Individual Differences in Overconfidence: A New Measurement Approach

Binnendyk, Jabin; Pennycook, Gordon

doi:10.2139/ssrn.4563382

2023

DOI: 10.2139/ssrn.4563382

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Individual Differences in Overconfidence: A New Measurement Approach

Jabin Binnendyk,

Gordon Pennycook

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2024

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Cited by 3 publications

References 81 publications

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Leveraging artificial intelligence to identify the psychological factors associated with conspiracy theory beliefs online

Kunst,

Gundersen,

Krysińska

et al. 2024

Nat Commun

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Given the profound societal impact of conspiracy theories, probing the psychological factors associated with their spread is paramount. Most research lacks large-scale behavioral outcomes, leaving factors related to actual online support for conspiracy theories uncertain. We bridge this gap by combining the psychological self-reports of 2506 Twitter (currently X) users with machine-learning classification of whether the textual data from their 7.7 million social media engagements throughout the pandemic supported six common COVID-19 conspiracy theories. We assess demographic factors, political alignment, factors derived from theory of reasoned action, and individual psychological differences. Here, we show that being older, self-identifying as very left or right on the political spectrum, and believing in false information constitute the most consistent risk factors; denialist tendencies, confidence in one’s ability to spot misinformation, and political conservativism are positively associated with support for one conspiracy theory. Combining artificial intelligence analyses of big behavioral data with self-report surveys can effectively identify and validate risk factors for phenomena evident in large-scale online behaviors.

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Leveraging artificial intelligence to identify the psychological factors associated with conspiracy theory beliefs online

Kunst,

Gundersen,

Krysińska

et al. 2024

Nat Commun

View full text Add to dashboard Cite

show abstract

Two components of individual differences in actively open-minded thinking standards: myside bias and uncertainty aversion

Baron

2024

Thinking & Reasoning

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Using an AI-powered “street epistemologist” chatbot and reflection tasks to diminish conspiracy theory beliefs

Meyer,

Enders,

Klofstad

et al. 2024

HKS Misinfo Review

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Social scientists, journalists, and policymakers are increasingly interested in methods to mitigate or reverse the public’s beliefs in conspiracy theories, particularly those associated with negative social consequences, including violence. We contribute to this field of research using an artificial intelligence (AI) intervention that prompts individuals to reflect on the uncertainties in their conspiracy theory beliefs. Conspiracy theory believers who interacted with our “street epistemologist” chatbot subsequently showed weaker conviction in their conspiracy theory beliefs; this was also the case for subjects who were asked to reflect on their beliefs without conversing with an AI chatbot. We found that encouraging believers to reflect on their uncertainties can weaken beliefs and that AI-powered interventions can help reduce epistemically unwarranted beliefs for some believers.

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Individual Differences in Overconfidence: A New Measurement Approach

Cited by 3 publications

References 81 publications

Leveraging artificial intelligence to identify the psychological factors associated with conspiracy theory beliefs online

Leveraging artificial intelligence to identify the psychological factors associated with conspiracy theory beliefs online

Two components of individual differences in actively open-minded thinking standards: myside bias and uncertainty aversion

Using an AI-powered “street epistemologist” chatbot and reflection tasks to diminish conspiracy theory beliefs

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