Online behavioral data, such as digital traces from social media, have the potential to allow researchers an unprecedented new window into human behavior in ecologically valid everyday contexts. However, research using such data is often purely observational, which limits its usefulness for identifying causal relationships. Here we review recent innovations in experimental approaches to studying online behavior, with a particular focus on research related to misinformation and political psychology. In hybrid lab-field studies, exposure to social-media content can be randomized, and the impact on attitudes and beliefs can be measured using surveys, or exposure to treatments can be randomized within survey experiments, and their impact on subsequent online behavior can be observed. In field experiments conducted on social media, randomized treatments can be administered directly to users in the online environment (e.g., via social-tie invitations, private messages, or public posts) without revealing that they are part of an experiment, and the effects on subsequent online behavior can then be observed. The strengths and weaknesses of each approach are discussed, along with practical advice and central ethical constraints on such studies.

在线行为数据，例如来自社交媒体的数字痕迹，有可能让研究人员在生态有效的日常环境中获得前所未有的人类行为新窗口。然而，使用此类数据的研究通常纯粹是观察性的，这限制了其识别因果关系的用处。在这里，我们回顾了研究在线行为的实验方法的最新创新，特别关注与错误信息和政治心理学相关的研究。在混合实验室实地研究中，接触社交媒体内容可以是随机的，对态度和信念的影响可以使用调查来衡量，或者可以在调查实验中随机接受治疗，它们对后续在线行为的影响可以是观察到的。在社交媒体上进行的实地实验中，随机治疗可以直接对在线环境中的用户进行（例如，通过社交联系邀请、私人消息或公开帖子），而无需透露它们是实验的一部分，然后可以观察对后续在线行为的影响。讨论了每种方法的优点和缺点，以及对此类研究的实用建议和核心伦理约束。