A Signal Detection Approach to Understanding Susceptibility to Misinformation

一种了解错误信息敏感性的信号检测方法

• 批准号: 2040684
• 负责人: Bertram Gawronski
• 金额: $ 42.39万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2040684&HistoricalAwards=false
• 关键词: Signal; Detection; Approach; Understanding; Susceptibility

One of the greatest challenges for the functioning of societies in the information age is the prevalence and impact of misinformation. Concerns over the impact of misinformation have grown considerably as the internet and social media provide a conduit for spreading information widely and rapidly, regardless of its veracity. The current project aims to investigate how people determine whether new information they encounter is correct or incorrect, and how people decide whether to share this information on social media. Using a formal modeling approach called Signal Detection Theory, the research focuses on three aspects of such judgments: (a) the ability to distinguish between correct and incorrect information, (b) general tendencies to treat information as correct vs. incorrect regardless of veracity, and (c) partisan bias involving a tendency to accept information that is consistent with one's personal beliefs and dismiss information that is inconsistent with one's personal beliefs. The findings are expected to provide valuable insights into why people might be susceptible to misinformation and how it might be possible to reduce the spread of misinformation.Toward this end, the current project investigates how cognitive and motivational factors jointly influence responses to correct and incorrect information. Across a series of 16 studies, the project addresses the following questions: How well can people distinguish between correct and incorrect information? When are decisions to share information on social media influenced by people's perceptions of accuracy? Does more elaborate thinking increase people's ability to distinguish between correct and incorrect information? How does elaborate thinking influence partisan bias in responses to belief-congruent and belief-incongruent information? How does greater confidence about one's personal values influence accuracy and partisan bias? How do echo chambers and prior exposure to information influence people's susceptibility to misinformation? How effective is debunking in reducing susceptibility to misinformation? How does the source of information influence responses to correct and incorrect information? How can partisan bias in responses to correct and incorrect information be reduced? Project activities also involve training students on using signal detection methods to investigate how people judge information. The project helps to address societal problems that stem from misinformation by investigating the psychological processes that make people susceptible to misinformation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

信息时代社会运作面临的最大挑战之一是错误信息的普遍存在和影响。由于互联网和社交媒体提供了广泛和迅速传播信息的渠道，无论其真实性如何，对错误信息影响的担忧大大增加。目前的项目旨在调查人们如何确定他们遇到的新信息是正确还是不正确，以及人们如何决定是否在社交媒体上分享这些信息。使用一种称为信号检测理论的正式建模方法，研究集中在此类判断的三个方面：（a）区分正确和不正确信息的能力，（B）将信息视为正确或不正确而不管其真实性的一般倾向，以及（c）一种倾向于接受与个人信仰相一致的信息而忽视不一致的信息的党派偏见与个人信仰的冲突这些发现有望为人们为什么容易受到错误信息的影响以及如何减少错误信息的传播提供有价值的见解。为此，目前的项目研究了认知和动机因素如何共同影响对正确和不正确信息的反应。在一系列的16项研究中，该项目解决了以下问题：人们如何区分正确和不正确的信息？在社交媒体上分享信息的决定何时会受到人们对准确性的看法的影响？更精细的思考是否会提高人们区分正确和错误信息的能力？精细思维如何影响对信念一致和信念不一致信息的反应中的党派偏见？对个人价值观的更大信心如何影响准确性和党派偏见？回音室和先前的信息暴露如何影响人们对错误信息的敏感性？揭穿真相在减少对错误信息的敏感性方面有多有效？信息来源如何影响对正确和不正确信息的反应？如何减少对正确和不正确信息的反应中的党派偏见？项目活动还包括培训学生使用信号检测方法来调查人们如何判断信息。该项目通过调查使人们容易受到错误信息影响的心理过程，帮助解决源于错误信息的社会问题。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A Signal Detection Approach to Understanding the Identification of Fake News

• DOI: 10.1177/1745691620986135
• 发表时间: 2021-07-15
• 期刊: PERSPECTIVES ON PSYCHOLOGICAL SCIENCE
• 影响因子: 12.6
• 作者: Batailler, Cedric;Brannon, Skylar M.;Gawronski, Bertram
• 通讯作者: Gawronski, Bertram