  We study the impact of content moderation policies in online communities. In
our theoretical model, a platform chooses a content moderation policy and
individuals choose whether or not to participate in the community according to
the fraction of user content that aligns with their preferences. The effects of
content moderation, at first blush, might seem obvious: it restricts speech on
a platform. However, when user participation decisions are taken into account,
its effects can be more subtle $\unicode{x2013}$ and counter-intuitive. For
example, our model can straightforwardly demonstrate how moderation policies
may increase participation and diversify content available on the platform. In
our analysis, we explore a rich set of interconnected phenomena related to
content moderation in online communities. We first characterize the
effectiveness of a natural class of moderation policies for creating and
sustaining stable communities. Building on this, we explore how
resource-limited or ideological platforms might set policies, how communities
are affected by differing levels of personalization, and competition between
platforms. Our model provides a vocabulary and mathematically tractable
framework for analyzing platform decisions about content moderation.
