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Stranger Danger! Cross-Community Interactions with Fringe Users Increase the Growth of Fringe Communities on Reddit (2310.12186v1)

Published 18 Oct 2023 in cs.SI and cs.AI

Abstract: Fringe communities promoting conspiracy theories and extremist ideologies have thrived on mainstream platforms, raising questions about the mechanisms driving their growth. Here, we hypothesize and study a possible mechanism: new members may be recruited through fringe-interactions: the exchange of comments between members and non-members of fringe communities. We apply text-based causal inference techniques to study the impact of fringe-interactions on the growth of three prominent fringe communities on Reddit: r/Incel, r/GenderCritical, and r/The_Donald. Our results indicate that fringe-interactions attract new members to fringe communities. Users who receive these interactions are up to 4.2 percentage points (pp) more likely to join fringe communities than similar, matched users who do not. This effect is influenced by 1) the characteristics of communities where the interaction happens (e.g., left vs. right-leaning communities) and 2) the language used in the interactions. Interactions using toxic language have a 5pp higher chance of attracting newcomers to fringe communities than non-toxic interactions. We find no effect when repeating this analysis by replacing fringe (r/Incel, r/GenderCritical, and r/The_Donald) with non-fringe communities (r/climatechange, r/NBA, r/leagueoflegends), suggesting this growth mechanism is specific to fringe communities. Overall, our findings suggest that curtailing fringe-interactions may reduce the growth of fringe communities on mainstream platforms.

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References (49)
  1. Understanding and supporting fathers and fatherhood on social media sites. In Proceedings of the 33rd annual ACM conference on human factors in computing systems, 1905–1914.
  2. Austin, P. C. 2011. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate behavioral research 46(3): 399–424.
  3. Preferential behavior in online groups. In Proceedings of the 2008 international conference on web search and data mining, 117–128.
  4. The PushShift Reddit dataset. In ’20Proceedings of the international AAAI conference on web and social media, volume 14, 830–839.
  5. Routledge handbook of conspiracy theories. Routledge.
  6. A social movement online community: Stormfront and the white nationalist movement. In Media, movements, and political change, 163–193. Emerald Group Publishing Limited.
  7. Quarantined! Examining the effects of a community-wide moderation intervention on Reddit. ACM Transactions on Computer-Human Interaction (TOCHI) 29(4): 1–26.
  8. You can’t stay here: The efficacy of reddit’s 2015 ban examined through hate speech. Proceedings of the ACM on Human-Computer Interaction 1(CSCW): 1–22.
  9. Facebook bans QAnon across its platforms. https://www.nbcnews.com/tech/tech-news/facebook-bans-qanon-across-its-platforms-n1242339.
  10. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 .
  11. Fine-tuning pretrained language models: Weight initializations, data orders, and early stopping. arXiv preprint arXiv:2002.06305 .
  12. Gelman, A. 2014. It’s not matching or regression; it’s matching and regression. URL https://statmodeling.stat.columbia.edu/2014/06/22/matching-regression-matching-regression/.
  13. Causal inference in statistics: A primer. John Wiley & Sons.
  14. Assessing the threat of incel violence. Studies in Conflict & Terrorism 43(7): 565–587.
  15. Do platform migrations compromise content moderation? evidence from r/the_donald and r/incels. Proceedings of the ACM on Human-Computer Interaction 5(CSCW2): 1–24.
  16. Why do people participate in small online communities? Proceedings of the ACM on Human-Computer Interaction 5(CSCW2): 1–25.
  17. Online hatred of women in the Incels. me forum: Linguistic analysis and automatic detection. Journal of Language Aggression and Conflict 7(2): 240–268.
  18. Evaluating the effectiveness of deplatforming as a moderation strategy on Twitter. Proceedings of the CSW2’21 on Human-Computer Interaction 5(CSCW2): 1–30.
  19. Jigsaw. 2022. Perspective API. https://perspectiveapi.com/.
  20. Kaitlyn, T. 2020. The Secret Internet of TERFs. https://www.theatlantic.com/technology/archive/2020/12/reddit-ovarit-the-donald/617320/. Accessed on 2022-08-26.
  21. MEGA X: molecular evolutionary genetics analysis across computing platforms. Molecular biology and evolution 35(6): 1547.
  22. Follow the (slash) dot: effects of feedback on new members in an online community. In Proceedings of the 2005 ACM International Conference on Supporting Group Work, 11–20.
  23. The Presentation of Health-Related Search Results and Its Impact on Negative Emotional Outcomes. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’13, 333–342. New York, NY, USA: Association for Computing Machinery. ISBN 9781450318990. doi:10.1145/2470654.2470702. URL https://doi.org/10.1145/2470654.2470702.
  24. City, self, network: transnational migrants and online identity work. In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing, 1502–1510.
  25. Encouraging participation in virtual communities through usability and sociability development: An empirical investigation. ACM SIGMIS Database: The DATABASE for Advances in Information Systems 42(3): 96–114.
  26. Lyons, M. N. 2017. Ctrl-alt-delete: The origins and ideology of the alternative right. Political Research Associates 20.
  27. Online conspiracy communities are more resilient to deplatforming. arXiv preprint arXiv:2303.12115 .
  28. Soros, child sacrifices, and 5G: understanding the spread of conspiracy theories on web communities. arXiv:2111.02187 .
  29. Linguistic inquiry and word count: LIWC 2001. Mahway: Lawrence Erlbaum Associates .
  30. Pathways through conspiracy: the evolution of conspiracy radicalization through engagement in online conspiracy discussions. In Proceedings of the International AAAI Conference on Web and Social Media, volume 16, 770–781.
  31. Building member attachment in online communities: Applying theories of group identity and interpersonal bonds. MIS quarterly 841–864.
  32. The evolution of the manosphere across the web. In Proceedings of the International AAAI Conference on Web and Social Media, volume 15, 196–207.
  33. Virtual community attraction: Why people hang out online. Journal of Computer-mediated communication 10(1): JCMC10110.
  34. Rosenbaum, P. R. 2005. Sensitivity analysis in observational studies. Encyclopedia of statistics in behavioral science .
  35. The central role of the propensity score in observational studies for causal effects. Biometrika 70(1): 41–55.
  36. Understanding online migration decisions following the banning of radical communities. In Proceedings of the 15th ACM Web Science Conference 2023, 251–259.
  37. Acti at evalita 2023: Overview of the conspiracy theory identification task. arXiv preprint arXiv:2307.06954 .
  38. Spillover of antisocial behavior from fringe platforms: The unintended consequences of community banning. In Proceedings of the International AAAI Conference on Web and Social Media, volume 17, 742–753.
  39. Conspiracies online: User discussions in a conspiracy community following dramatic events. In Proceedings of the International AAAI Conference on Web and Social Media, volume 12.
  40. Schmid, A. P. 2013. Radicalisation, de-radicalisation, counter-radicalisation: A conceptual discussion and literature review. ICCT research paper 97(1): 22.
  41. Quantifying how hateful communities radicalize online users. In 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 139–146. IEEE.
  42. Make reddit great again: assessing community effects of moderation interventions on r/the_donald. Proceedings of the ACM on Human-Computer Interaction 6(CSCW2): 1–28.
  43. Generalists and specialists: Using community embeddings to quantify activity diversity in online platforms. In The World Wide Web Conference, 1954–1964.
  44. Quantifying social organization and political polarization in online platforms. Nature .
  45. Washington Post. 2020. ‘Reddit closes long-running forum supporting President Trump after years of policy violations’. URL https://www.washingtonpost.com/technology/2020/06/29/reddit-closes-long-running-forum-supporting-president-trump-after-years-policy-violations/.
  46. Adjusting for confounders with text: Challenges and an empirical evaluation framework for causal inference. In ICWSM.
  47. Williams, C. 2020. The ontological woman: A history of deauthentication, dehumanization, and violence. The Sociological Review 68(4): 718–734.
  48. Community identity and user engagement in a multi-community landscape. In Proceedings of the international AAAI conference on web and social media, volume 11, 377–386.
  49. Bertscore: Evaluating text generation with bert. arXiv:1904.09675 .
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