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Guided rewiring of social networks reduces polarization and accelerates collective action (2309.12141v1)
Published 21 Sep 2023 in physics.soc-ph, cond-mat.stat-mech, cs.SI, nlin.AO, and q-bio.PE
Abstract: Global challenges like climate change may be considered as collective action problems that require sufficient cooperation with pro-mitigation norms, soon enough to be effective. Socio-political polarization is a barrier to collective action. Prior agent-based models of behavioural change on structured networks in a shared socio-political environment have shown that polarization emerges naturally in such systems and that the speed of consensus formation is limited by the rate at which polarized clusters can be dissolved. Here we study how guided social link rewiring affects the speed of network depolarization. We investigate rewiring algorithms representing random meetings, introduction by mutual acquaintances, and bridging between socially distant communities. We find that building lasting links between polarized individuals and communities can accelerate consensus formation when the sociopolitical environment is favourable. This strengthens the evidence that promoting connection between polarized communities could accelerate collective action on urgent global challenges.
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Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. 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Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Janssen, M.: Evolution of cooperation in a one-shot prisoner’s dilemma based on recognition of trustworthy and untrustworthy agents. Journal of Economic Behavior & Organization 65, 458–471 (2008). https://doi.org/10.1016/j.jebo.2006.02.004 (4) Ostrom, E.: Beyond markets and states: Polycentric governance of complex economic systems. American Economic Review 100(3), 641–672 (2010). https://doi.org/10.1257/aer.100.3.641 (5) Williges, K., Meyer, L.H., Steininger, K.W., Kirchengast, G.: Fairness critically conditions the carbon budget allocation across countries. Global Environmental Change 74, 102481 (2022). https://doi.org/10.1016/j.gloenvcha.2022.102481 (6) Scheffer, M., Carpenter, S., Lenton, T., Bascompte, J., Brock, W., Dakos, V., van de Koppel, J., van de Leemput, I., Levin, S., Nes, E., Pascual, M., Vandermeer, J.: Anticipating critical transitions. Science (New York, N.Y.) 338, 344–348 (2012). https://doi.org/10.1126/science.1225244 (7) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Ostrom, E.: Beyond markets and states: Polycentric governance of complex economic systems. American Economic Review 100(3), 641–672 (2010). https://doi.org/10.1257/aer.100.3.641 (5) Williges, K., Meyer, L.H., Steininger, K.W., Kirchengast, G.: Fairness critically conditions the carbon budget allocation across countries. Global Environmental Change 74, 102481 (2022). https://doi.org/10.1016/j.gloenvcha.2022.102481 (6) Scheffer, M., Carpenter, S., Lenton, T., Bascompte, J., Brock, W., Dakos, V., van de Koppel, J., van de Leemput, I., Levin, S., Nes, E., Pascual, M., Vandermeer, J.: Anticipating critical transitions. Science (New York, N.Y.) 338, 344–348 (2012). https://doi.org/10.1126/science.1225244 (7) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williges, K., Meyer, L.H., Steininger, K.W., Kirchengast, G.: Fairness critically conditions the carbon budget allocation across countries. Global Environmental Change 74, 102481 (2022). https://doi.org/10.1016/j.gloenvcha.2022.102481 (6) Scheffer, M., Carpenter, S., Lenton, T., Bascompte, J., Brock, W., Dakos, V., van de Koppel, J., van de Leemput, I., Levin, S., Nes, E., Pascual, M., Vandermeer, J.: Anticipating critical transitions. Science (New York, N.Y.) 338, 344–348 (2012). https://doi.org/10.1126/science.1225244 (7) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Scheffer, M., Carpenter, S., Lenton, T., Bascompte, J., Brock, W., Dakos, V., van de Koppel, J., van de Leemput, I., Levin, S., Nes, E., Pascual, M., Vandermeer, J.: Anticipating critical transitions. Science (New York, N.Y.) 338, 344–348 (2012). https://doi.org/10.1126/science.1225244 (7) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. 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Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. 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Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. 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Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. 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Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williges, K., Meyer, L.H., Steininger, K.W., Kirchengast, G.: Fairness critically conditions the carbon budget allocation across countries. Global Environmental Change 74, 102481 (2022). https://doi.org/10.1016/j.gloenvcha.2022.102481 (6) Scheffer, M., Carpenter, S., Lenton, T., Bascompte, J., Brock, W., Dakos, V., van de Koppel, J., van de Leemput, I., Levin, S., Nes, E., Pascual, M., Vandermeer, J.: Anticipating critical transitions. Science (New York, N.Y.) 338, 344–348 (2012). https://doi.org/10.1126/science.1225244 (7) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. 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International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Scheffer, M., Carpenter, S., Lenton, T., Bascompte, J., Brock, W., Dakos, V., van de Koppel, J., van de Leemput, I., Levin, S., Nes, E., Pascual, M., Vandermeer, J.: Anticipating critical transitions. Science (New York, N.Y.) 338, 344–348 (2012). https://doi.org/10.1126/science.1225244 (7) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. 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Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. 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Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. 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Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williges, K., Meyer, L.H., Steininger, K.W., Kirchengast, G.: Fairness critically conditions the carbon budget allocation across countries. Global Environmental Change 74, 102481 (2022). https://doi.org/10.1016/j.gloenvcha.2022.102481 (6) Scheffer, M., Carpenter, S., Lenton, T., Bascompte, J., Brock, W., Dakos, V., van de Koppel, J., van de Leemput, I., Levin, S., Nes, E., Pascual, M., Vandermeer, J.: Anticipating critical transitions. Science (New York, N.Y.) 338, 344–348 (2012). https://doi.org/10.1126/science.1225244 (7) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Scheffer, M., Carpenter, S., Lenton, T., Bascompte, J., Brock, W., Dakos, V., van de Koppel, J., van de Leemput, I., Levin, S., Nes, E., Pascual, M., Vandermeer, J.: Anticipating critical transitions. Science (New York, N.Y.) 338, 344–348 (2012). https://doi.org/10.1126/science.1225244 (7) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. 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Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. 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Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Brownstein, M., Kelly, D., Madva, A.: Individualism, structuralism, and climate change. Environmental Communication 16, 269–288 (2022). https://doi.org/10.1080/17524032.2021.1982745 (8) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. 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Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Griskevicius, V., Cantú, S.M., van Vugt, M.: The Evolutionary Bases for Sustainable Behavior: Implications for Marketing, Policy, and Social Entrepreneurship. Journal of Public Policy & Marketing 31(1), 115–128 (2012). https://doi.org/10.1509/jppm.11.040 (9) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) IPCC: In: Pörtner, H.O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., Rama, B. (eds.) Summary for Policymakers. Cambridge University Press, Cambridge, UK (2022). In Press (10) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. 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International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. 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Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. 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Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. 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Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. 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PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Ringsmuth, A.K., Otto, I.M., van den Hurk, B., Lahn, G., Reyer, C.P.O., Carter, T.R., Magnuszewski, P., Monasterolo, I., Aerts, J.C.J.H., Benzie, M., Campiglio, E., Fronzek, S., Gaupp, F., Jarzabek, L., Klein, R.J.T., Knaepen, H., Mechler, R., Mysiak, J., Sillmann, J., Stuparu, D., West, C.: Lessons from covid-19 for managing transboundary climate risks and building resilience. Climate Risk Management 35, 100395 (2022). https://doi.org/10.1016/j.crm.2022.100395 (11) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. 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International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. 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PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. 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Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. 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(2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
- Vasconcelos, V., Constantino, S., Dannenberg, A., Lumkowsky, M., Weber, E., Levin, S.: Segregation and clustering of preferences erode socially beneficial coordination. Proceedings of the National Academy of Sciences 118, 2102153118 (2021). https://doi.org/10.1073/pnas.2102153118 (12) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pawloff, A., Formayer, H., Schlatzer, M.: Contrarians’ – Their Role in the Debate on Climate Change (Global Warming) and Their Influence on the Austrian Policy Making Process. https://www.klimafonds.gv.at (13) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. 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Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Carothers, T., O’Donohue, A.: Democracies Divided: The Global Challenge of Political Polarization. Brookings Institution Press, Washington D.C. (2019) (14) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. 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Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. 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Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gladston, I., Wing, T.: Social media and public polarization over climate change in the united states, 10 (2019) (15) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. 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Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. 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Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. 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International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. 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Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) McCarty, N.: Polarization: What Everyone Needs to Know. Oxford University Press, Oxford, UK (2019). https://doi.org/10.1093/wentk/9780190867782.001.0001 (16) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. 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Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R., Daymude, J., Forrest, S.: Preventing extreme polarization of political attitudes. Proceedings of the National Academy of Sciences 118, 2102139118 (2021). https://doi.org/10.1073/pnas.2102139118 (17) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. American Behavioral Scientist 62(1), 43–58 (2018). https://doi.org/10.1177/0002764218756924 (18) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Stavrakakis, Y.: Paradoxes of polarization: Democracy’s inherent division and the (anti-) populist challenge. 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Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gowdy, J.: Behavioral economics and climate change policy. Journal of Economic Behavior & Organization 68, 632–644 (2008). https://doi.org/10.1016/j.jebo.2008.06.011 (19) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. 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Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. 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AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. 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PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. 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Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. 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Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Tavoni, A., Schlüter, M., Levin, S.: The survival of the conformist: Social pressure and renewable resource management. Journal of Theoretical Biology 299, 152–161 (2012). https://doi.org/10.1016/j.jtbi.2011.07.003 (20) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Williams, H.T.P., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change 32, 126–138 (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006 (21) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. 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International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. 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AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. 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PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nguyen, C.T.: Echo chambers and epistemic bubbles. Episteme 17(2), 141–161 (2020). https://doi.org/10.1017/epi.2018.32 (22) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. 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Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., Galesic, M.: Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour 3(10), 1078–1087 (2019). https://doi.org/10.1038/s41562-019-0677-4 (23) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Fotouhi, B., Momeni, N., Allen, B., Nowak, M.: Conjoining Uncooperative Societies Facilitates Evolution of Cooperation. Nature Human Behaviour 2, 492–499 (2018). https://doi.org/10.1038/s41562-018-0368-6 (24) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. 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Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. 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Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. 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PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. 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Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. 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Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
- Andersson, D., Bratsberg, S., Ringsmuth, A.K., de Wijn, A.S.: Dynamics of collective action to conserve a large common-pool resource. Scientific Reports 11(1), 9208 (2021) 2012.00892. https://doi.org/10.1038/s41598-021-87109-x (25) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Santos, F., Lelkes, Y., Levin, S.: Link recommendation algorithms and dynamics of polarization in online social networks. Proceedings of the National Academy of Sciences 118, 2102141118 (2021). https://doi.org/10.1073/pnas.2102141118 (26) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Dunbar, R.I.M.: The anatomy of friendship. Trends in Cognitive Sciences 22(1), 32–51 (2018). https://doi.org/10.1016/j.tics.2017.10.004 (27) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Otto, I., Donges, J., Cremades, R., Bhowmik, A., Hewitt, R., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S., Lenferna, A., Morán, N., Vuuren, D., Schellnhuber, H.: Social tipping dynamics for stabilizing earth’s climate by 2050. Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. 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The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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Proceedings of the National Academy of Sciences 117, 201900577 (2020). https://doi.org/10.1073/pnas.1900577117 (28) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Gardiner, S.M.: A Perfect Moral Storm: The Ethical Tragedy of Climate Change. Environmental Ethics and Science Policy Series. Oxford University Press, Oxford, UK (2011). https://doi.org/10.1093/acprof:oso/9780195379440.001.0001 (29) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.M.: Homophily, networks, and critical mass: Solving the start-up problem in large group collective action. Rationality and Society (2013). https://doi.org/10.1177/1043463112473734 (30) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. 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PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
- Centola, D.: The spread of behavior in an online social network experiment. Science (New York, N.Y.) 329, 1194–7 (2010). https://doi.org/10.1126/science.1185231 (31) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
- Guilbeault, D., Centola, D.: Topological measures for identifying and predicting the spread of complex contagions. Nature Communications 12(1), 4430 (2021). https://doi.org/10.1038/s41467-021-24704-6 (32) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Pham, T.M., Alexander, A.C., Korbel, J., Hanel, R., Thurner, S.: Balance and fragmentation in societies with homophily and social balance. Scientific Reports 11, 17188 (2021). https://doi.org/10.1038/s41598-021-96065-5 (33) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
- Axelrod, R.: The dissemination of culture: A model with local convergence and global polarization. The Journal of Conflict Resolution 41, 203–226 (1997) (34) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Reviews of Modern Physics 81 (2007). https://doi.org/10.1103/RevModPhys.81.591 (35) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
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PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. 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AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
- Andersson, D.: Simple models for complex nonequilibrium problems in nanoscale friction and network dynamics. PhD thesis, Stockholm University (2020) (36) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Holme, P., Kim, B.J.: Growing scale-free networks with tunable clustering. Physical Review E 65(2), 026107 (2002). https://doi.org/10.1103/PhysRevE.65.026107 (37) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. 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E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
- Blondel, V., Guillaume, J.-L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory and Experiment 2008 (2008). https://doi.org/10.1088/1742-5468/2008/10/P10008 (38) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
- Mallinson, D., Hatemi, P.: Correction: The effects of information and social conformity on opinion change. PLOS ONE 15, 0230728 (2020). https://doi.org/10.1371/journal.pone.0230728 (39) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
- Nasiri, E., Berahmand, K., Li, Y.: A new link prediction in multiplex networks using topologically biased random walks. Chaos, Solitons & Fractals 151, 111230 (2021). https://doi.org/10.1016/j.chaos.2021.1112 (40) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
- Kozma, B., Barrat, A.: Consensus formation on adaptive networks. Physical review. E, Statistical, nonlinear, and soft matter physics 77, 016102 (2008). https://doi.org/10.1103/PhysRevE.77.016102 (41) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018) Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)
- Crawford, C., Nanda Kumar, R., Sen, S.: Resisting exploitation through rewiring in social networks: Social welfare increase using parity, sympathy and reciprocity. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. AAMAS ’18, pp. 1915–1917. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2018)