Researchers across many disciplines seek to understand how misinformation spreads with a view toward limiting its impact. One important question in this research is how people determine whether a given piece of news is real or fake. In the current article, we discuss the value of signal detection theory (SDT) in disentangling two distinct aspects in the identification of fake news: (a) ability to accurately distinguish between real news and fake news and (b) response biases to judge news as real or fake regardless of news veracity. The value of SDT for understanding the determinants of fake-news beliefs is illustrated with reanalyses of existing data sets, providing more nuanced insights into how partisan bias, cognitive reflection, and prior exposure influence the identification of fake news. Implications of SDT for the use of source-related information in the identification of fake news, interventions to improve people’s skills in detecting fake news, and the debunking of misinformation are discussed.

许多学科的研究人员试图了解错误信息是如何传播的，以限制其影响。这项研究中的一个重要问题是人们如何确定一条给定的新闻是真实的还是虚假的。在本文中，我们讨论了信号检测理论 (SDT) 在区分假新闻识别中两个不同方面的价值：(a) 准确区分真实新闻和假新闻的能力，以及 (b) 判断新闻的响应偏差无论新闻真实性如何，都是真的还是假的。通过对现有数据集的重新分析，说明了 SDT 在理解假新闻信念的决定因素方面的价值，为党派偏见、认知反思和先前曝光如何影响假新闻的识别提供了更细致的见解。