Motivated Bias in Detecting Climate Change Misinformation

Date
2024-01-03
Authors
Fong, Mia
John, Richard
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2066
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Misinformation undermines a shared understanding of the complexity of climate change and impedes public support for mitigation policies to build resilience. This paper reports an empirical study (N=398) of U.S. adults’ accuracy and bias in identifying true and false headlines related to climate change. The headlines were evenly balanced such that half were true and half false (fake news); likewise, half emphasized, and half questioned the urgency of climate change. Respondents indicated whether they believed each of the 24 headlines was true or false and provided confidence ratings. Pooled ROC analyses suggested moderate accuracy (AUC = 0.68) and a bias (c=0.09) favoring accuracy for false headlines (specificity=0.67) and attenuating the accuracy rate for true headlines (sensitivity = 0.60). Regression analysis on individual Signal Detection Theory (SDT) performance measures revealed that political liberalism and actively open-minded thinking (AOT) positively predicted accuracy (AUC), while climate change anxiety (CCAS) positively predicted bias.
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Disaster Information, Resilience, for Emergency and Crisis Technologies, fake news, item response theory, roc analysis, signal detection theory, truth detection
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10 pages
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Proceedings of the 57th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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