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The Crisis of Public Health and Infodemic: Analyzing Belief Structure of Fake News about COVID-19 Pandemic

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  • Seoyong Kim

    (Department of Public Administration, Ajou University, Suwon 16499, Korea)

  • Sunhee Kim

    (Department of Local Government Administration, Gangneung-Wonju National University, Gangneung-si 25457, Korea)

Abstract

False information about COVID-19 is being produced and disseminated on a large scale, impeding efforts to rapidly impose quarantines. Thus, in addition to the COVID-19 pandemic itself, an infodemic related with it is leading to social crises. This study therefore investigates who believes the misinformation that is being produced in the context of COVID-19. We choose two main factors—risk perception factor, so called psychometric paradigm, and communication factor—as independent variables that can affect belief in misinformation related to COVID-19. The results show that, among psychometric variables, perceived risk and stigma positively impact belief in fake news, whereas perceived benefit and trust have negative effects. Among communication factors, source credibility and the quantity of information reduce belief in fake news, whereas the credibility of information sources increases these beliefs. Stigma has the greatest explanatory power among the variables, followed by health status, heuristic information processing, trust, and subjective social class.

Suggested Citation

  • Seoyong Kim & Sunhee Kim, 2020. "The Crisis of Public Health and Infodemic: Analyzing Belief Structure of Fake News about COVID-19 Pandemic," Sustainability, MDPI, vol. 12(23), pages 1-23, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:23:p:9904-:d:451753
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    References listed on IDEAS

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    Cited by:

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    2. Greta Castellini & Mariarosaria Savarese & Guendalina Graffigna, 2021. "Online Fake News about Food: Self-Evaluation, Social Influence, and the Stages of Change Moderation," IJERPH, MDPI, vol. 18(6), pages 1-13, March.
    3. Geunsik Kim & Seoyong Kim & Eunjung Hwang, 2021. "Searching for Evidence-Based Public Policy and Practice: Analysis of the Determinants of Personal/Public Adaptation and Mitigation Behavior against Particulate Matter by Focusing on the Roles of Risk ," IJERPH, MDPI, vol. 18(2), pages 1-22, January.
    4. Maria José Sá & Ana Isabel Santos & Sandro Serpa & Carlos Miguel Ferreira, 2021. "Digitainability—Digital Competences Post-COVID-19 for a Sustainable Society," Sustainability, MDPI, vol. 13(17), pages 1-22, August.
    5. Raj, Chahat & Meel, Priyanka, 2022. "People lie, actions Don't! Modeling infodemic proliferation predictors among social media users," Technology in Society, Elsevier, vol. 68(C).
    6. 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.
    7. Mohammad Daradkeh, 2022. "Analyzing Sentiments and Diffusion Characteristics of COVID-19 Vaccine Misinformation Topics in Social Media: A Data Analytics Framework," International Journal of Business Analytics (IJBAN), IGI Global, vol. 9(3), pages 1-22, July.
    8. Andrew P. Weiss & Ahmed Alwan & Eric P. Garcia & Antranik T. Kirakosian, 2021. "Toward a Comprehensive Model of Fake News: A New Approach to Examine the Creation and Sharing of False Information," Societies, MDPI, vol. 11(3), pages 1-17, July.

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