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The rise and fall of WallStreetBets: social roles and opinion leaders across the GameStop saga (2403.05876v1)

Published 9 Mar 2024 in physics.soc-ph and cs.CY

Abstract: Nowadays human interactions largely take place on social networks, with online users' behavior often falling into a few general typologies or "social roles". Among these, opinion leaders are of crucial importance as they have the ability to spread an idea or opinion on a large scale across the network, with possible tangible consequences in the real world. In this work we extract and characterize the different social roles of users within the Reddit WallStreetBets community, around the time of the GameStop short squeeze of January 2021 -- when a handful of committed users led the whole community to engage in a large and risky financial operation. We identify the profiles of both average users and of relevant outliers, including opinion leaders, using an iterative, semi-supervised classification algorithm, which allows us to discern the characteristics needed to play a particular social role. The key features of opinion leaders are large risky investments and constant updates on a single stock, which allowed them to attract a large following and, in the case of GameStop, ignite the interest of the community. Finally, we observe a substantial change in the behavior and attitude of users after the short squeeze event: no new opinion leaders are found and the community becomes less focused on investments. Overall, this work sheds light on the users' roles and dynamics that led to the GameStop short squeeze, while also suggesting why WallStreetBets no longer wielded such large influence on financial markets, in the aftermath of this event.

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References (65)
  1. Conte, R. et al. Manifesto of computational social science. \JournalTitleThe European Physical Journal Special Topics 214, 325–346, DOI: 10.1140/epjst/e2012-01697-8 (2012).
  2. Lazer, D. et al. Computational social science. \JournalTitleScience 323, 721–723, DOI: 10.1126/science.1167742 (2009). https://www.science.org/doi/pdf/10.1126/science.1167742.
  3. Forecasting managerial turnover through e-mail based social network analysis. \JournalTitleComputers in Human Behavior 71, 343–352, DOI: https://doi.org/10.1016/j.chb.2017.02.017 (2017).
  4. Clemente, R. D. et al. Sequences of purchases in credit card data reveal lifestyles in urban populations. \JournalTitleNature Communications 9, DOI: 10.1038/s41467-018-05690-8 (2018).
  5. Characterizing dense urban areas from mobile phone-call data: Discovery and social dynamics. In 2010 IEEE Second International Conference on Social Computing, 241–248, DOI: 10.1109/SocialCom.2010.41 (2010).
  6. On the Uniqueness of Web Browsing History Patterns. \JournalTitleAnnals of Telecommunications - annales des télécommunications DOI: 10.1007/s12243-013-0392-5 (2013).
  7. Statistical physics of social dynamics. \JournalTitleRev. Mod. Phys. 81, 591–646, DOI: 10.1103/RevModPhys.81.591 (2009).
  8. Cimini, G. et al. The statistical physics of real-world networks. \JournalTitleNature Reviews Physics 1, 58–71, DOI: 10.1038/s42254-018-0002-6 (2019).
  9. Twenty-five years of social media: A review of social media applications and definitions from 1994 to 2019. \JournalTitleCyberpsychology, Behavior, and Social Networking 24, 215–222, DOI: 10.1089/cyber.2020.0134 (2021).
  10. Bail, C. A. et al. Exposure to opposing views on social media can increase political polarization. \JournalTitleProceedings of the National Academy of Sciences 115, 9216–9221, DOI: 10.1073/pnas.1804840115 (2018). https://www.pnas.org/doi/pdf/10.1073/pnas.1804840115.
  11. Lazer, D. M. J. et al. The science of fake news. \JournalTitleScience 359, 1094–1096, DOI: 10.1126/science.aao2998 (2018). https://www.science.org/doi/pdf/10.1126/science.aao2998.
  12. The echo chamber effect on social media. \JournalTitleProceedings of the National Academy of Sciences 118, e2023301118, DOI: 10.1073/pnas.2023301118 (2021). https://www.pnas.org/doi/pdf/10.1073/pnas.2023301118.
  13. Student and environmental protests in chile: The role of social media. \JournalTitlePolitics 35, 151–171, DOI: 10.1111/1467-9256.12072 (2015). https://doi.org/10.1111/1467-9256.12072.
  14. Khondker, H. H. Role of the new media in the arab spring. \JournalTitleGlobalizations 8, 675–679, DOI: 10.1080/14747731.2011.621287 (2011). https://doi.org/10.1080/14747731.2011.621287.
  15. Reddit’s self-organised bull runs: Social contagion and asset prices. INET Oxford Working Papers 2021-04, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford (2021).
  16. Recurring patterns in online social media interactions during highly engaging events (2023). 2306.14735.
  17. Patterns of routes of administration and drug tampering for nonmedical opioid consumption: Data mining and content analysis of reddit discussions. \JournalTitleJ Med Internet Res 23, e21212, DOI: 10.2196/21212 (2021).
  18. The reddit politosphere: A large-scale text and network resource of online political discourse. \JournalTitleProceedings of the International AAAI Conference on Web and Social Media 16, 1259–1267, DOI: 10.1609/icwsm.v16i1.19377 (2022).
  19. Extracting cryptocurrency price movements from the reddit network sentiment. In 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA), 500–505, DOI: 10.1109/ICMLA.2019.00093 (2019).
  20. Chohan, U. W. Yolo capitalism. \JournalTitleSSRN 432, DOI: http://dx.doi.org/10.2139/ssrn.3775127 (2022).
  21. Self-induced consensus of reddit users to characterise the gamestop short squeeze. \JournalTitleScientific Reports 12, DOI: 10.1038/s41598-022-17925-2 (2022).
  22. Lucchini, L. et al. From reddit to wall street: the role of committed minorities in financial collective action. \JournalTitleRoyal Society Open Science 9, DOI: 10.1098/rsos.211488 (2022).
  23. Zheng, X. et al. Game starts at gamestop: Characterizing the collective behaviors and social dynamics in the short squeeze episode. \JournalTitleIEEE Transactions on Computational Social Systems 9, 45–58, DOI: 10.1109/TCSS.2021.3122260 (2022).
  24. Social informedness and investor sentiment in the gamestop short squeeze. \JournalTitleElectronic Markets 33, DOI: 10.1007/s12525-023-00632-9 (2023).
  25. Haq, E.-U. et al. Short, colorful, and irreverent! a comparative analysis of new users on wallstreetbets during the gamestop short-squeeze. In Companion Proceedings of the Web Conference 2022, WWW ’22, 52–61, DOI: 10.1145/3487553.3524202 (Association for Computing Machinery, New York, NY, USA, 2022).
  26. Biddle, B. J. Recent developments in role theory. \JournalTitleAnnual Review of Sociology 12, 67–92, DOI: 10.1146/annurev.so.12.080186.000435 (1986). https://doi.org/10.1146/annurev.so.12.080186.000435.
  27. Welser, H. T. et al. Finding social roles in wikipedia. In Proceedings of the 2011 IConference, iConference ’11, 122–129, DOI: 10.1145/1940761.1940778 (Association for Computing Machinery, New York, NY, USA, 2011).
  28. A typology of social networking sites users. \JournalTitleInternational Journal of Web Based Communities 7, 28–51, DOI: 10.1504/IJWBC.2011.038124 (2011).
  29. Using social network analysis and social capital to identify user roles on polarized political conversations on twitter. \JournalTitleSocial Media + Society 5, 2056305119848745, DOI: 10.1177/2056305119848745 (2019). https://doi.org/10.1177/2056305119848745.
  30. Centrality in heterogeneous social networks for lurkers detection: an approach based on hypergraphs. \JournalTitleConcurrency and Computation Practice and Experience 30, DOI: 10.1002/cpe.4188 (2017).
  31. Understanding user behavior in online social networks: A survey. ieee communications magazine, 51(9), 144-150. \JournalTitleCommunications Magazine, IEEE 51, 144–150, DOI: 10.1109/MCOM.2013.6588663 (2013).
  32. A density-based algorithm for discovering clusters in large spatial databases with noise. In Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, KDD’96, 226–231 (AAAI Press, 1996).
  33. Katz, E. The two-step flow of communication: An up-to-date report on an hypothesis. \JournalTitleThe Public Opinion Quarterly 21, 61–78 (1957).
  34. Identification of influential online social network users based on multi-features. \JournalTitleInternational Journal of Pattern Recognition and Artificial Intelligence 30, 1659015, DOI: 10.1142/S0218001416590151 (2016). https://doi.org/10.1142/S0218001416590151.
  35. Examining characteristics of opinion leaders in social media: A motivational approach. \JournalTitleSocial Media + Society 2, DOI: 10.1177/2056305116665858 (2016).
  36. Identifying opinion leaders on social networks through milestones definition. \JournalTitleIEEE Access 7, 75670 – 75677, DOI: 10.1109/ACCESS.2019.2922155 (2019).
  37. Finfluencers: Opinion makers or opinion followers? \JournalTitleECIS 2023 Research Papers 432, DOI: https://aisel.aisnet.org/ecis2023_rp/432 (2023).
  38. Wallstreetbets: Positions or ban (2021). 2101.12110.
  39. Whiteman, L. Why shares of palantir technologies soared higher in november. \JournalTitleThe Motley Fool (2020).
  40. Identifying social roles in reddit using network structure. In Proceedings of the 23rd International Conference on World Wide Web, WWW ’14 Companion, 615–620, DOI: 10.1145/2567948.2579231 (Association for Computing Machinery, New York, NY, USA, 2014).
  41. van Mierlo, T. The 1% rule in four digital health social networks: An observational study. \JournalTitleJ Med Internet Res 16, e33, DOI: 10.2196/jmir.2966 (2014).
  42. Gagnon, T. The disinhibition of reddit users. \JournalTitleAdele Richardson’s Spring 2013 ENC 1102 (2013).
  43. Reddit’s veil of anonymity: Predictors of engagement and participation in media environments with hostile reputations. \JournalTitleSocial Media + Society 4, 2056305118810216, DOI: 10.1177/2056305118810216 (2018). https://doi.org/10.1177/2056305118810216.
  44. On spectral clustering: Analysis and an algorithm. In Proceedings of the 14th International Conference on Neural Information Processing Systems: Natural and Synthetic, NIPS’01, 849–856 (MIT Press, Cambridge, MA, USA, 2001).
  45. Viualizing data using t-sne. \JournalTitleJournal of Machine Learning Research 9, 2579–2605 (2008).
  46. Visualizing the signatures of social roles in online discussion groups. \JournalTitleJournal of Social Structure 8, 1–31 (2007).
  47. Richmond, V. P. Monomorphic and Polymorphic Opinion Leadership within a Relatively Closed Communication System. \JournalTitleHuman Communication Research 6, 111–116, DOI: 10.1111/j.1468-2958.1980.tb00131.x (2006). https://academic.oup.com/hcr/article-pdf/6/2/111/22344577/jhumcom0111.pdf.
  48. The role of the social-identity function of attitudes in consumer innovativeness and opinion leadership. \JournalTitleJournal of Economic Psychology 21, 233–252, DOI: 10.1016/S0167-4870(00)00003-9 (2000).
  49. The king and summers opinion leadership scale: Revision and refinement. \JournalTitleJournal of Business Research 31, 55–64, DOI: 10.1016/0148-2963(94)90046-9 (1994).
  50. Identifying opinion leaders in social networks with topic limitation. \JournalTitleCluster Computing 20, 2403–2413 (2017).
  51. Identifying the most influential topic-sensitive opinion leaders in online review communities. In 2016 IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA), 330–335, DOI: 10.1109/ICCCBDA.2016.7529579 (2016).
  52. Identification of influencers - measuring influence in customer networks. \JournalTitleDecision Support Systems 46, 233–253, DOI: https://doi.org/10.1016/j.dss.2008.06.007 (2008).
  53. Detecting opinion leaders and trends in online social networks. In Proceedings of the 2nd ACM Workshop on Social Web Search and Mining, SWSM ’09, 65–68, DOI: 10.1145/1651437.1651448 (Association for Computing Machinery, New York, NY, USA, 2009).
  54. McDowell, J. The amc short squeeze explanation. \JournalTitleTradingSim Blog (2022).
  55. The pushshift reddit dataset (2020). 2001.08435.
  56. Smythe, C. The r/wallstreetbets glossary: A field guide to apes, stonks, tendies, and more. \JournalTitleThe Business of Business (2021).
  57. Vader: A parsimonious rule-based model for sentiment analysis of social media text. \JournalTitleProceedings of the International AAAI Conference on Web and Social Media 8, 216–225, DOI: 10.1609/icwsm.v8i1.14550 (2014).
  58. Characterization of the twitter @replies network: Are user ties social or topical? In Proceedings of the 2nd International Workshop on Search and Mining User-Generated Contents, SMUC ’10, 63–70, DOI: 10.1145/1871985.1871996 (Association for Computing Machinery, New York, NY, USA, 2010).
  59. Statistical analysis of the social network and discussion threads in slashdot. In Proceedings of the 17th International Conference on World Wide Web, WWW ’08, 645–654, DOI: 10.1145/1367497.1367585 (Association for Computing Machinery, New York, NY, USA, 2008).
  60. Pedregosa, F. et al. Scikit-learn: Machine learning in Python. \JournalTitleJournal of Machine Learning Research 12, 2825–2830 (2011).
  61. Anomaly detection in temperature data using dbscan algorithm. In 2011 International Symposium on Innovations in Intelligent Systems and Applications, 91–95, DOI: 10.1109/INISTA.2011.5946052 (2011).
  62. Application of dbscan to anomaly detection in airport terminals. In 2020 3rd International Conference on Engineering Technology and its Applications (IICETA), 112–116, DOI: 10.1109/IICETA50496.2020.9318876 (2020).
  63. Anomaly detection in bitcoin prices using dbscan algorithm. \JournalTitleEuropean Journal of Science and Technology 2020, 436–443, DOI: 10.31590/ejosat.araconf57 (2020).
  64. A cluster separation measure. \JournalTitleIEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-1, 224–227, DOI: 10.1109/TPAMI.1979.4766909 (1979).
  65. Newman, M. E. J. Mixing patterns in networks. \JournalTitlePhysical Review E 67, DOI: 10.1103/physreve.67.026126 (2003).

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