Tell me the Truth: Separating Fact from Fiction in Social Media Following Extreme Events

Date
2021-01-05
Authors
Byrd, Katie
John, Richard
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Abstract
With increased reliance on social media to spread important information during extreme events, users’ reported inability to distinguish fact from fiction is a growing concern. This experiment (N=398) tests whether feedback training improves performance in identifying true and false social media content during extreme events. Respondents completed two sets of 16 binary classification judgments (true or false) of actual social media posts following either natural disasters or soft-target terror attacks. Respondents randomly assigned to the feedback training condition received feedback after each of the 16 training judgments, while those assigned to the control condition did not receive any feedback following the training judgments. Feedback training did not increase social media content classification performance for either natural disasters or soft-target terror events. Individuals’ performance for correctly identifying false content was negatively related to self- identified political conservatism and was positively related to a measure of cognitive reflection.
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Keywords
Decision Making in Online Social Networks, fake news, feedback learning, natural disasters, (soft-target) terrorism, truth detection
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