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.

翻译：内容审核是一种广泛采用的策略，用于防止社交媒体平台上不规范信息的传播。尽管已有大量研究致力于开发自动化模型以支持内容审核的决策过程，但将在线社区规则整合到内容审核中的研究仍明显不足。本研究通过提出一种基于社区规则的内容审核框架来填补这一空白，该框架直接将社区规则整合到用户生成内容的审核中。我们使用从两个领域收集的数据集进行的实验结果表明，基于该框架的模型在所有评估指标上均优于基线模型。特别是，融入社区规则显著提升了模型在内容审核中的性能。本研究的结果对于提高在线社区中内容审核模型的有效性和泛化能力具有重要的研究意义和实践价值。