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Reddit administrators have generally struggled to prevent or contain suchdiscourse for several reasons including: (1) the inability for a handful ofhuman administrators to track and react to millions of posts and comments perday and (2) fear of backlash as a consequence of administrative decisions toban or quarantine hateful communities. Consequently, as shown in our backgroundresearch, administrative actions (community bans and quarantines) are oftentaken in reaction to media pressure following offensive discourse within acommunity spilling into the real world with serious consequences. In thispaper, we investigate the feasibility of proactive moderation on Reddit --i.e., proactively identifying communities at risk of committing offenses thatpreviously resulted in bans for other communities. Proactive moderationstrategies show promise for two reasons: (1) they have potential to narrow downthe communities that administrators need to monitor for hateful content and (2)they give administrators a scientific rationale to back their administrativedecisions and interventions. Our work shows that communities are constantlyevolving in their user base and topics of discourse and that evolution intohateful or dangerous (i.e., considered bannable by Reddit administrators)communities can often be predicted months ahead of time. This makes proactivemoderation feasible. Further, we leverage explainable machine learning to helpidentify the strongest predictors of evolution into dangerous communities. Thisprovides administrators with insights into the characteristics of communitiesat risk becoming dangerous or hateful. Finally, we investigate, at scale, theimpact of participation in hateful and dangerous subreddits and theeffectiveness of community bans and quarantines on the behavior of members ofthese communities.

To Act or React: Investigating Proactive Strategies For Online Community Moderation