Let Community Rules Be Reflected in Online Content Moderation
This research addresses the gap in content moderation for online communities by incorporating community-specific rules, offering practical improvements for social media platforms.
The study tackled the problem of integrating online community rules into content moderation by proposing a community rule-based framework, which demonstrated superior performance over baseline models across all evaluation metrics in experiments with datasets from two domains.
Content moderation is a widely used strategy to prevent the dissemination of irregular information on social media platforms. Despite extensive research on developing automated models to support decision-making in content moderation, there remains a notable scarcity of studies that integrate the rules of online communities into content moderation. This study addresses this gap by proposing a community rule-based content moderation framework that directly integrates community rules into the moderation of user-generated content. Our experiment results with datasets collected from two domains demonstrate the superior performance of models based on the framework to baseline models across all evaluation metrics. In particular, incorporating community rules substantially enhances model performance in content moderation. The findings of this research have significant research and practical implications for improving the effectiveness and generalizability of content moderation models in online communities.