A Signal Detection Approach to Understanding the Identification of Fake News
A Signal Detection Approach to Understanding the Identification of Fake News
复制标题
DOI：
10.1177/1745691620986135
复制
发表时间：
2021-07-15
影响因子：
12.6
通讯作者：
Gawronski, Bertram
中科院分区：
文献类型：
--
作者：
Batailler, Cedric;Brannon, Skylar M.;Gawronski, Bertram
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假的。在这篇文章中，我们讨论了信号检测理论（SDT）在识别假新闻中的两个不同方面的价值：（a）准确区分真实的新闻和假新闻的能力，以及（B）判断新闻是真实的还是假新闻而不管新闻真实性的反应偏差。SDT对于理解假新闻信念的决定因素的价值通过对现有数据集的重新分析来说明，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。SDT的使用源相关的信息在识别假新闻，干预措施，以提高人们的技能，发现假新闻，揭穿错误信息的影响进行了讨论。
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.