Beyond Trial-and-Error: Predicting User Abandonment After a Moderation Intervention

Understand

Current content moderation follows a reactive, trial-and-error approach, where interventions are applied and their effects are only measured post-hoc.

• In contrast, we introduce a proactive, predictive approach that enables moderators to anticipate the impact of their actions before implementation.
• We propose and tackle the new task of predicting user abandonment following a moderation intervention.
• We study the reactions of 16,540 users to a massive ban of online communities on Reddit, training a set of binary classifiers to identify those users who would abandon the platform after the intervention -- a problem of great practical relevance.