Identifying successful approaches for reducing the belief and spread of online misinformation is of great importance. Social media companies currently rely largely on professional fact-checking as their primary mechanism for identifying falsehoods. However, professional fact-checking has notable limitations regarding coverage and speed. In this article, we summarize research suggesting that the "wisdom of crowds" can be harnessed successfully to help identify misinformation at scale. Despite potential concerns about the abilities of laypeople to assess information quality, recent evidence demonstrates that aggregating judgments of groups of laypeople, or crowds, can effectively identify low-quality news sources and inaccurate news posts: Crowd ratings are strongly correlated with fact-checker ratings across a variety of studies using different designs, stimulus sets, and subject pools. We connect these experimental findings with recent attempts to deploy crowdsourced fact-checking in the field, and we close with recommendations and future directions for translating crowdsourced ratings into effective interventions.

中文翻译：

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群体可以有效地大规模识别错误信息。


确定减少在线错误信息的信念和传播的成功方法非常重要。社交媒体公司目前主要依靠专业的事实核查作为识别虚假信息的主要机制。然而，专业的事实核查在覆盖范围和速度方面存在明显的局限性。在本文中，我们总结了研究，表明可以成功地利用“群体的智慧”来帮助大规模识别错误信息。尽管人们可能担心外行评估信息质量的能力，但最近的证据表明，综合外行群体或人群的判断可以有效识别低质量的新闻来源和不准确的新闻帖子：人群评级与事实核查评级密切相关使用不同设计、刺激集和主题库的各种研究。我们将这些实验结果与最近在该领域部署众包事实核查的尝试联系起来，最后我们提出了将众包评级转化为有效干预措施的建议和未来方向。