Are Proactive Interventions for Reddit Communities Feasible?

Authors

  • Hussam Habib University of Iowa
  • Maaz Bin Musa University of Iowa
  • Muhammad Fareed Zaffar Lahore University of Management sciences
  • Rishab Nithyanand University of Iowa

DOI:

https://doi.org/10.1609/icwsm.v16i1.19290

Keywords:

Organizational and group behavior mediated by social media; interpersonal communication mediated by social media, Social network analysis; communities identification; expertise and authority discovery, Trend identification and tracking; time series forecasting, Text categorization; topic recognition; demographic/gender/age identification

Abstract

Reddit has found its communities playing a prominent role in originating and propagating problematic sociopolitical discourse. Reddit administrators have generally struggled to prevent or contain such discourse for several reasons including: (1) the inability for a handful of human administrators to track and react to millions of posts and comments per day and (2) fear of backlash as a consequence of administrative decisions to ban or quarantine hateful communities. Consequently, administrative actions (community bans and quarantines) are often taken only when problematic discourse within a community spills over into the real world with serious consequences. In this paper, we investigate the feasibility of deploying tools to proactively identify problematic communities on Reddit. Proactive identification strategies show promise for three reasons: (1) they have potential to reduce the manual efforts required to track communities for problematic content, (2) they give administrators a scientific rationale to back their decisions and interventions, and (3) they facilitate early and more nuanced interventions (than banning or quarantining) to mitigate problematic discourse.

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Published

2022-05-31

How to Cite

Habib, H., Musa, M. B., Zaffar, M. F., & Nithyanand, R. (2022). Are Proactive Interventions for Reddit Communities Feasible?. Proceedings of the International AAAI Conference on Web and Social Media, 16(1), 264-274. https://doi.org/10.1609/icwsm.v16i1.19290