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Accuracy and social motivations shape judgements of (mis)information

Author

Listed:
  • Steve Rathje

    (University of Cambridge)

  • Jon Roozenbeek

    (University of Cambridge)

  • Jay J. Bavel

    (New York University)

  • Sander Linden

    (University of Cambridge)

Abstract

The extent to which belief in (mis)information reflects lack of knowledge versus a lack of motivation to be accurate is unclear. Here, across four experiments (n = 3,364), we motivated US participants to be accurate by providing financial incentives for correct responses about the veracity of true and false political news headlines. Financial incentives improved accuracy and reduced partisan bias in judgements of headlines by about 30%, primarily by increasing the perceived accuracy of true news from the opposing party (d = 0.47). Incentivizing people to identify news that would be liked by their political allies, however, decreased accuracy. Replicating prior work, conservatives were less accurate at discerning true from false headlines than liberals, yet incentives closed the gap in accuracy between conservatives and liberals by 52%. A non-financial accuracy motivation intervention was also effective, suggesting that motivation-based interventions are scalable. Altogether, these results suggest that a substantial portion of people’s judgements of the accuracy of news reflects motivational factors.

Suggested Citation

  • Steve Rathje & Jon Roozenbeek & Jay J. Bavel & Sander Linden, 2023. "Accuracy and social motivations shape judgements of (mis)information," Nature Human Behaviour, Nature, vol. 7(6), pages 892-903, June.
    • Handle: RePEc:nat:nathum:v:7:y:2023:i:6:d:10.1038_s41562-023-01540-w
    DOI: 10.1038/s41562-023-01540-w
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    References listed on IDEAS

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    Cited by:

    1. Diego Marino Fages, 2024. "Motivated Forecasts: Experimental Evidence from the Presidential Elections in Argentina," Discussion Papers 2024-08, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    2. Cun Fu & Jinru Zhang & Xin Kang, 2024. "True or false? Linguistic and demographic factors influence veracity judgment of COVID-19 rumors," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-7, December.

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