  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, as shown in our background
research, administrative actions (community bans and quarantines) are often
taken in reaction to media pressure following offensive discourse within a
community spilling into the real world with serious consequences. In this
paper, we investigate the feasibility of proactive moderation on Reddit --
i.e., proactively identifying communities at risk of committing offenses that
previously resulted in bans for other communities. Proactive moderation
strategies show promise for two reasons: (1) they have potential to narrow down
the communities that administrators need to monitor for hateful content and (2)
they give administrators a scientific rationale to back their administrative
decisions and interventions. Our work shows that communities are constantly
evolving in their user base and topics of discourse and that evolution into
hateful or dangerous (i.e., considered bannable by Reddit administrators)
communities can often be predicted months ahead of time. This makes proactive
moderation feasible. Further, we leverage explainable machine learning to help
identify the strongest predictors of evolution into dangerous communities. This
provides administrators with insights into the characteristics of communities
at risk becoming dangerous or hateful. Finally, we investigate, at scale, the
impact of participation in hateful and dangerous subreddits and the
effectiveness of community bans and quarantines on the behavior of members of
these communities.
