  To address the widespread problem of uncivil behavior, many online discussion
platforms employ human moderators to take action against objectionable content,
such as removing it or placing sanctions on its authors. This reactive paradigm
of taking action against already-posted antisocial content is currently the
most common form of moderation, and has accordingly underpinned many recent
efforts at introducing automation into the moderation process. Comparatively
less work has been done to understand other moderation paradigms -- such as
proactively discouraging the emergence of antisocial behavior rather than
reacting to it -- and the role algorithmic support can play in these paradigms.
In this work, we investigate such a proactive framework for moderation in a
case study of a collaborative setting: Wikipedia Talk Pages. We employ a mixed
methods approach, combining qualitative and design components for a holistic
analysis. Through interviews with moderators, we find that despite a lack of
technical and social support, moderators already engage in a number of
proactive moderation behaviors, such as preemptively intervening in
conversations to keep them on track. Further, we explore how automation could
assist with this existing proactive moderation workflow by building a prototype
tool, presenting it to moderators, and examining how the assistance it provides
might fit into their workflow. The resulting feedback uncovers both strengths
and drawbacks of the prototype tool and suggests concrete steps towards further
developing such assisting technology so it can most effectively support
moderators in their existing proactive moderation workflow.
