跟随提示而不依赖预算：关于虚假信息追随者未改变追随网络的实地实验
Follow Nudges without Budges: A Field Experiment on Misinformation Followers Didn't Change Follow Networks
AI总结：
本研究通过实地实验探讨数字广告是否能促使虚假信息追随者转向准确信息源，发现基于说服性信息的广告效果显著，但整体成本效益不高。
摘要：
数字广告能否鼓励接触到不准确信息源的用户去关注准确的信息源？我们对X（前推特）进行了大规模的实地实验（N=28582），研究对象是那些关注传播健康虚假信息的账户的用户。参与者被暴露在四种广告处理上，这些处理在两个维度上有所变化：中性信息消息与具有独立价值观的说服性信息消息，以及请求关注健康机构与请求关注健康影响者。我们将这种基于广告的社会网络干预称为“跟随提示”。具有说服性信息消息要求关注知名健康机构的广告，其点击率显著高于所有其他条件（Bonferroni校正成对检验，所有p<0.001）。然而，考虑到所有处理中的总体低点击率以及X上的数字广告基础设施的高成本，我们得出结论，我们提出的方法——至少在目前的基于广告的格式下——不是改善在线信息环境的一种有效手段。我们讨论了在X上进行大规模实验所面临的挑战，这发生在平台所有权变更后，随后对研究目的的数据访问进行了限制。
英文摘要：
Can digital ads encourage users exposed to inaccurate information sources to follow accurate ones? We conduct a large-scale field experiment (N=28,582) on X, formerly Twitter, with users who follow accounts that spread health misinformation. Participants were exposed to four ad treatments varied on two dimensions: a neutral message versus a persuasive message appealing to values of independence, and a request to follow a health institution versus a request to follow a health influencer. We term this ad-based, social network intervention a follow nudge. The ad with a persuasive message to follow a well-known health institution generated significantly higher click-through rates than all other conditions (Bonferroni-corrected pairwise tests, all p<0.001). Given the overall low click-through rate across treatments and the high cost of digital advertising infrastructure on X, however, we conclude that our proposed intervention -- at least in its current ad-based format -- is not a cost-effective means to improve information environments online. We discuss challenges faced when conducting large-scale experiments on X following the platform's ownership change and subsequent restrictions on data access for research purposes.
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