Papers
Topics
Authors
Recent
Search
2000 character limit reached

Characterizing User Archetypes and Discussions on Scored.co

Published 31 Jul 2024 in cs.SI, cs.AI, and cs.CL | (2407.21753v2)

Abstract: In recent years, the proliferation of social platforms has drastically transformed the way individuals interact, organize, and share information. In this scenario, we experience an unprecedented increase in the scale and complexity of interactions and, at the same time, little to no research about some fringe social platforms. In this paper, we present a multi-dimensional framework for characterizing nodes and hyperedges in social hypernetworks, with a focus on the understudied alt-right platform Scored.co. Our approach integrates the possibility of studying higher-order interactions, thanks to the hypernetwork representation, and various node features such as user activity, sentiment, and toxicity, with the aim to define distinct user archetypes and understand their roles within the network. Utilizing a comprehensive dataset from Scored.co, we analyze the dynamics of these archetypes over time and explore their interactions and influence within the community. The framework's versatility allows for detailed analysis of both individual user behaviors and broader social structures. Our findings highlight the importance of higher-order interactions in understanding social dynamics, offering new insights into the roles and behaviors that emerge in complex online environments.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (47)
  1. Hypernetwork science via high-order hypergraph walks. EPJ Data Science, 9(1):16, 2020.
  2. Analysis of online social network connections for identification of influential users: Survey and open research issues. ACM Computing Surveys (CSUR), 51(1):1–37, 2018. ACM.
  3. Dynamical patterns of cattle trade movements. PloS one, 6(5):e19869, 2011.
  4. How dramatic events can affect emotionality in social posting: the impact of covid-19 on reddit. Future Internet, 13(2):29, 2021. MDPI.
  5. Networks beyond pairwise interactions: Structure and dynamics. Physics Reports, 874:1–92, 2020. Elsevier.
  6. Node classification in social networks. Social network data analytics, pages 115–148, 2011.
  7. Hyper-edges and multidimensional centrality. Social networks, 26(3):189–203, 2004. Elsevier.
  8. R. Brendel and H. Krawczyk. Primary role identification in dynamic social networks. In Proc. of 2011 International Conference on Computational Aspects of Social Networks (CASoN 2011), pages 54–59, 2011. IEEE.
  9. C. Buntain and J. Golbeck. Identifying social roles in reddit using network structure. In Proc. of the 23rd international conference on World Wide Web (WWW 2014), pages 615–620, 2014. ACM.
  10. Investigating reddit to detect subreddit and author stereotypes and to evaluate author assortativity. Journal of Information Science, 48(6):783–810, 2022. SAGE.
  11. F. Cauteruccio and Y. Kou. Investigating the emotional experiences in esports spectatorship: The case of league of legends. Information Processing & Management, 60(6):103516, 2023.
  12. The great ban: Efficacy and unintended consequences of a massive deplatforming operation on reddit. In Companion Publication of the 16th ACM Web Science Conference, pages 85–93, 2024.
  13. Detecting bots in social-networks using node and structural embeddings. Journal of Big Data, 10(1):119, 2023. Springer.
  14. Redefining event types and group evolution in temporal data. arXiv preprint arXiv:2403.06771, 2024.
  15. Attributed stream hypergraphs: temporal modeling of node-attributed high-order interactions. Applied Network Science, 8(1):31, 2023.
  16. Scored.co hypernetwork dataset, 2024.
  17. A. Failla and G. Rossetti. “i’m in the bluesky tonight”: Insights from a year worth of social data. arXiv preprint arXiv:2404.18984, 2024.
  18. J. Hacker and K. Riemer. Identification of user roles in enterprise social networks: method development and application. Business & Information Systems Engineering, 63(4):367–387, 2021. Springer.
  19. J. Haidt and C. Joseph. Intuitive ethics: How innately prepared intuitions generate culturally variable virtues. Daedalus, 133(4):55–66, 2004.
  20. L. Hanu and Unitary team. Detoxify. Github. https://github.com/unitaryai/detoxify, 2020.
  21. The extended moral foundations dictionary (emfd): Development and applications of a crowd-sourced approach to extracting moral intuitions from text. Behavior research methods, 53:232–246, 2021.
  22. Identifying node role in social network based on multiple indicators. PloS one, 9(8):e103733, 2014. Public Library of Science San Francisco.
  23. C. Hutto and E. Gilbert. Vader: A parsimonious rule-based model for sentiment analysis of social media text. In Proc. of the International AAAI Conference on Web and Social Media (ICWSM 2014), volume 8, pages 216–225, 2014.
  24. Toward understanding and evaluating structural node embeddings. ACM Transactions on Knowledge Discovery from Data (TKDD), 16(3):1–32, 2021. ACM.
  25. Understanding social roles in an online community of volatile practice: A study of user experience practitioners on reddit. ACM Transactions on Social Computing, 1(4):1–22, 2018. ACM.
  26. Computational social science. Science, 323(5915):721–723, 2009.
  27. A. Mehrabian and J. A. Russell. An approach to environmental psychology. the MIT Press, 1974.
  28. The koo dataset: An indian microblogging platform with global ambitions. In Proceedings of the International AAAI Conference on Web and Social Media, volume 18, pages 1991–2002, 2024.
  29. A. Mekacher and A. Papasavva. ” i can’t keep it up.” a dataset from the defunct voat. co news aggregator. In Proceedings of the International AAAI Conference on Web and Social Media, volume 16, pages 1302–1311, 2022.
  30. S. Mohammad. Obtaining reliable human ratings of valence, arousal, and dominance for 20,000 english words. In Proceedings of the 56th annual meeting of the association for computational linguistics (volume 1: Long papers), pages 174–184, 2018.
  31. Crowdsourcing a word–emotion association lexicon. Computational intelligence, 29(3):436–465, 2013.
  32. The shape of collaborations. EPJ Data Science, 6:1–16, 2017. Springer.
  33. The shape of collaborations. EPJ Data Science, 6:1–16, 2017.
  34. idrama-scored-2024: A dataset of the scored social media platform from 2020 to 2023. In Proceedings of the International AAAI Conference on Web and Social Media, volume 18, pages 2014–2024, 2024.
  35. R. Plutchik. A general psychoevolutionary theory of emotion. In Theories of emotion, pages 3–33. Elsevier, 1980.
  36. D. Quelle and A. Bovet. Bluesky: Network topology, polarisation, and algorithmic curation. arXiv preprint arXiv:2405.17571, 2024.
  37. Using social network analysis and social capital to identify user roles on polarized political conversations on twitter. Social media+ society, 5(2):2056305119848745, 2019. SAGE.
  38. Multi-scale attributed node embedding. Journal of Complex Networks, 9(2):cnab014, 2021. Oxford University Press.
  39. Fundamental structures of dynamic social networks. Proceedings of the national academy of sciences, 113(36):9977–9982, 2016. National Academy of Sciences.
  40. A. Singhal. Modern information retrieval: A brief overview. IEEE Data Engineering Bullettin, 24(4):35–43, 2001.
  41. Of collaborative learning team: An approach for emergent leadership roles identification by using social network analysis. In Proc. of Technologies for E-Learning and Digital Entertainment: First International Conference, pages 745–754, 2006. Springer.
  42. The why, how, and when of representations for complex systems. SIAM Review, 63(3):435–485, 2021.
  43. Identification of important nodes in directed biological networks: A network motif approach. PloS one, 9(8):e106132, 2014.
  44. The fair guiding principles for scientific data management and stewardship. Scientific data, 3(1):1–9, 2016.
  45. Social media for intelligent public information and warning in disasters: An interdisciplinary review. International Journal of Information Management, 49:190–207, 2019.
  46. Network representation learning: from preprocessing, feature extraction to node embedding. ACM Computing Surveys (CSUR), 55(2):1–35, 2022.
  47. User role identification based on social behavior and networking analysis for information dissemination. Future Generation Computer Systems, 96:639–648, 2019. Elsevier.

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.