Social media platforms face increasing scrutiny over the rapid spread of misinformation. In response, many have adopted community-based content moderation systems, including Community Notes (formerly Birdwatch) on X (formerly Twitter), Footnotes on TikTok, and Facebook's Community Notes initiative. However, research shows that the current design of these systems can allow political biases to influence both the development of notes and the rating processes, reducing their overall effectiveness. We hypothesize that enabling users to collaborate on writing notes, rather than relying solely on individually authored notes, can enhance their overall quality. To test this idea, we conducted an online experiment in which participants jointly authored notes on political posts. Our results show that teams produce notes that are rated as more helpful than individually written notes. We also find that politically diverse teams perform better when evaluating Republican posts, while group composition does not affect perceived note quality for Democrat posts. However, the advantage of collaboration diminishes when team members are aware of one another's political affiliations. Taken together, these findings underscore the complexity of community-based content moderation and highlight the importance of understanding group dynamics and political diversity when designing more effective moderation systems.

翻译：社交媒体平台因虚假信息的快速传播而面临日益严格的审查。为此，许多平台采用了基于社区的内容审核系统，包括X（原Twitter）的社区笔记（原Birdwatch）、TikTok的脚注以及Facebook的社区笔记计划。然而，研究表明，这些系统当前的设计可能使政治偏见影响笔记的撰写和评分过程，从而降低其整体有效性。我们假设，允许用户协作撰写笔记，而非仅依赖个人独立撰写的笔记，能够提升笔记的整体质量。为验证这一假设，我们开展了一项在线实验，参与者共同为政治性帖子撰写笔记。结果显示，团队撰写的笔记被评价为比个人撰写的笔记更有帮助。我们还发现，政治多元化的团队在评估共和党帖子时表现更佳，而团队构成对民主党帖子的笔记质量感知没有影响。然而，当团队成员知晓彼此的政治立场时，协作带来的优势会减弱。综上所述，这些发现揭示了社区内容审核的复杂性，并强调了在设计更有效的审核系统时，理解群体动态和政治多样性的重要性。