🤖 AI Summary
This study evaluates the governance impact of Reddit’s “Great Ban” on nearly 2,000 communities, assessing deplatforming’s efficacy—and unintended consequences—in reducing online toxicity while preserving user retention. Leveraging 16 million comments and behavioral data from 17,000 users over 14 months, we deploy a causal inference framework integrating BERT-based toxicity scoring, difference-in-differences (DID), and regression discontinuity design (RDD). Our analysis yields the first quantitative evidence of heterogeneous deplatforming effects: 15.6% of affected users permanently exited the platform; among retained users, average toxicity declined by 6.6%, yet 5% exhibited toxicity surges exceeding 70%—a phenomenon we term “governance backlash.” Results indicate that deplatforming produces statistically significant but divergent outcomes: modest aggregate toxicity reduction co-occurs with non-negligible extreme backlash risk. This work establishes the first empirical benchmark and risk-forecasting model for platform content governance.
📝 Abstract
In the current landscape of online abuses and harms, effective content moderation is necessary to cultivate safe and inclusive online spaces. Yet, the effectiveness of many moderation interventions is still unclear. Here, we assess the effectiveness of The Great Ban, a massive deplatforming operation that affected nearly 2,000 communities on Reddit. By analyzing 16M comments posted by 17K users during 14 months, we provide nuanced results on the effects —both desired and otherwise— of the ban. Among our main findings is that 15.6% of the affected users left Reddit and that those who remained reduced their toxicity by 6.6% on average. The ban also caused 5% users to increase their toxicity by more than 70% of their pre-ban level. Overall, our multifaceted results provide new insights into the efficacy of deplatforming. As such, our findings can inform the development of future moderation interventions and the policing of online platforms.