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.

翻译：我们研究在线社区中内容审核政策的影响。在我们的理论模型中，平台选择一项内容审核政策，而个体则根据符合其偏好的用户内容比例来决定是否参与社区。内容审核的效果乍看之下似乎显而易见：它限制了平台上的言论。然而，考虑到用户的参与决策时，其效果可能更为微妙——甚至违反直觉。例如，我们的模型可以直接说明审核政策如何可能增加参与度，并使平台上的内容多样化。在分析中，我们探索了与在线社区内容审核相关的一系列相互关联的现象。我们首先刻画了一类自然审核政策在创建和维持稳定社区方面的有效性。在此基础上，我们探讨了资源有限或意识形态导向的平台如何制定政策，不同个性化水平如何影响社区，以及平台之间的竞争。我们的模型为分析平台关于内容审核的决策提供了一个术语体系和数学上可处理的框架。