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Why do people spread false information online? The effects of message and viewer characteristics on self-reported likelihood of sharing social media disinformation

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  • Tom Buchanan

Abstract

Individuals who encounter false information on social media may actively spread it further, by sharing or otherwise engaging with it. Much of the spread of disinformation can thus be attributed to human action. Four studies (total N = 2,634) explored the effect of message attributes (authoritativeness of source, consensus indicators), viewer characteristics (digital literacy, personality, and demographic variables) and their interaction (consistency between message and recipient beliefs) on self-reported likelihood of spreading examples of disinformation. Participants also reported whether they had shared real-world disinformation in the past. Reported likelihood of sharing was not influenced by authoritativeness of the source of the material, nor indicators of how many other people had previously engaged with it. Participants’ level of digital literacy had little effect on their responses. The people reporting the greatest likelihood of sharing disinformation were those who thought it likely to be true, or who had pre-existing attitudes consistent with it. They were likely to have previous familiarity with the materials. Across the four studies, personality (lower Agreeableness and Conscientiousness, higher Extraversion and Neuroticism) and demographic variables (male gender, lower age and lower education) were weakly and inconsistently associated with self-reported likelihood of sharing. These findings have implications for strategies more or less likely to work in countering disinformation in social media.

Suggested Citation

  • Tom Buchanan, 2020. "Why do people spread false information online? The effects of message and viewer characteristics on self-reported likelihood of sharing social media disinformation," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-33, October.
  • Handle: RePEc:plo:pone00:0239666
    DOI: 10.1371/journal.pone.0239666
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    Cited by:

    1. Kerim Peren Arin & Juan A. Lacomba & Francisco Lagos & Deni Mazrekaj & Marcel Thum, 2021. "Misperceptions and Fake News during the Covid-19 Pandemic," CESifo Working Paper Series 9066, CESifo.
    2. Khan, Nuzaina & Rand, David & Shurchkov, Olga, 2024. "He Said, She Said: Who Gets Believed When Spreading (Mis)Information," IZA Discussion Papers 17282, Institute of Labor Economics (IZA).
    3. Hamby, Anne & Kim, Hongmin & Spezzano, Francesca, 2024. "Sensational stories: The role of narrative characteristics in distinguishing real and fake news and predicting their spread," Journal of Business Research, Elsevier, vol. 170(C).
    4. Adrian Kwek & Luke Peh & Josef Tan & Jin Xing Lee, 2023. "Distractions, analytical thinking and falling for fake news: A survey of psychological factors," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    5. K. Peren Arin & Umair Khalil & Deni Mazrekaj & Marcel Thum, 2023. "Terrorism and Misperceptions: Evidence from Europe," CESifo Working Paper Series 10476, CESifo.
    6. Kai Li & Jie Li & Fen Zhou, 2022. "The Effects of Personality Traits on Online Rumor Sharing: The Mediating Role of Fear of COVID-19," IJERPH, MDPI, vol. 19(10), pages 1-13, May.
    7. Andreea Nistor & Eduard Zadobrischi, 2022. "The Influence of Fake News on Social Media: Analysis and Verification of Web Content during the COVID-19 Pandemic by Advanced Machine Learning Methods and Natural Language Processing," Sustainability, MDPI, vol. 14(17), pages 1-24, August.
    8. Yossiri Yossatorn & Theerapong Binali & Cathy Weng & Regina Juchun Chu, 2023. "Investigating the Relationships Among LINE Users’ Concerns, Motivations for Information Sharing Intention and Information Sharing Behavior," SAGE Open, , vol. 13(3), pages 21582440231, August.

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