{"title":"Mindsets and politically motivated reasoning about fake news","authors":"Jonas Ludwig, Joseph Sommer","doi":"10.1007/s11031-024-10067-0","DOIUrl":null,"url":null,"abstract":"<p>False information may be published with the intention of misleading the public, and such fake news is often difficult to detect. Ideological fake news may pose a particular challenge, as people may be less able to detect false information that supports their prior beliefs. The difficulty of detecting fake news with an ideological slant may be compounded if people are motivated to defend their beliefs. Building on the mindset theory of action phases, we investigated motivational states as moderators of people’s ability to detect fake news. We tested two competing predictions to study the cognitive and motivational processes implicated in fake news detection. Both predictions concern an ideological belief bias, where people tend to accept information that agrees with their partisan identities and to reject information that disagrees with them. First, motivated reasoning accounts posit that deliberation should reinforce the ideological belief bias because reasoning primarily serves to defend and rationalize one’s own position. An opposing view, based on dual-process theory, assumes that deliberation attenuates the ideological belief bias by facilitating an unbiased assessment of new information. An online experiment (<i>N</i> = 497) tested these competing accounts. Participants were induced with deliberative/implemental/control mindsets prior to rating the veracity of (true/fake) news headlines. Some headlines favored a Republican view; others leaned toward a Democrat perspective. Based on self-reported political preference (Democrat vs. Republican), headlines were categorized as congruent or incongruent with participants’ political views. Consistent with an ideological belief bias, participants accepted more congruent than incongruent news, and they were more likely to fail to detect favorable fake news. In the main analysis, mindsets did not moderate the ideological belief bias, but showed interesting relationships with cognitive reflection and dishonest behavior. Further exploration using signal-detection theory suggested that the deliberative mindset might be associated with increased skepticism, thereby promoting fake news detection.</p>","PeriodicalId":48282,"journal":{"name":"Motivation and Emotion","volume":"13 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Motivation and Emotion","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1007/s11031-024-10067-0","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PSYCHOLOGY, EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
False information may be published with the intention of misleading the public, and such fake news is often difficult to detect. Ideological fake news may pose a particular challenge, as people may be less able to detect false information that supports their prior beliefs. The difficulty of detecting fake news with an ideological slant may be compounded if people are motivated to defend their beliefs. Building on the mindset theory of action phases, we investigated motivational states as moderators of people’s ability to detect fake news. We tested two competing predictions to study the cognitive and motivational processes implicated in fake news detection. Both predictions concern an ideological belief bias, where people tend to accept information that agrees with their partisan identities and to reject information that disagrees with them. First, motivated reasoning accounts posit that deliberation should reinforce the ideological belief bias because reasoning primarily serves to defend and rationalize one’s own position. An opposing view, based on dual-process theory, assumes that deliberation attenuates the ideological belief bias by facilitating an unbiased assessment of new information. An online experiment (N = 497) tested these competing accounts. Participants were induced with deliberative/implemental/control mindsets prior to rating the veracity of (true/fake) news headlines. Some headlines favored a Republican view; others leaned toward a Democrat perspective. Based on self-reported political preference (Democrat vs. Republican), headlines were categorized as congruent or incongruent with participants’ political views. Consistent with an ideological belief bias, participants accepted more congruent than incongruent news, and they were more likely to fail to detect favorable fake news. In the main analysis, mindsets did not moderate the ideological belief bias, but showed interesting relationships with cognitive reflection and dishonest behavior. Further exploration using signal-detection theory suggested that the deliberative mindset might be associated with increased skepticism, thereby promoting fake news detection.
期刊介绍:
Motivation and Emotion publishes articles on human motivational and emotional phenomena that make theoretical advances by linking empirical findings to underlying processes. Submissions should focus on key problems in motivation and emotion, and, if using non-human participants, should contribute to theories concerning human behavior. Articles should be explanatory rather than merely descriptive, providing the data necessary to understand the origins of motivation and emotion, to explicate why, how, and under what conditions motivational and emotional states change, and to document that these processes are important to human functioning.A range of methodological approaches are welcome, with methodological rigor as the key criterion. Manuscripts that rely exclusively on self-report data are appropriate, but published articles tend to be those that rely on objective measures (e.g., behavioral observations, psychophysiological responses, reaction times, brain activity, and performance or achievement indicators) either singly or combination with self-report data.The journal generally does not publish scale development and validation articles. However, it is open to articles that focus on the post-validation contribution that a new measure can make. Scale development and validation work therefore may be submitted if it is used as a necessary prerequisite to follow-up studies that demonstrate the importance of the new scale in making a theoretical advance.