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Refueling a Quiet Fire: Old Truthers and New Discontent in the Wake of Covid-19

Author

Listed:
  • Gabriele Beccari
  • Matilde Giaccherini
  • Joanna Kopinska
  • Gabriele Rovigatti
Abstract
This paper investigates the factors that contributed to the proliferation of online COVID skepticism on Twitter across Italian municipalities. We demonstrate that socio-demographic factors are likely to mitigate the emergence of skepticism, while populist political leanings were more likely to foster it. Furthermore, we find that the presence of pre-COVID anti-vax sentiment, represented by old "truthers" on Twitter, amplifies online COVID skepticism in local communities. Additionally, exploiting the spatial variation in economic restrictive policies with severe implications for suspended workers belonging to non-essential economic sectors, we find that COVID skepticism spreads more in municipalities significantly affected by this economic lockdown. Finally, the diffusion of COVID skepticism is positively associated with COVID vaccine hesitancy.

Suggested Citation

  • Gabriele Beccari & Matilde Giaccherini & Joanna Kopinska & Gabriele Rovigatti, 2023. "Refueling a Quiet Fire: Old Truthers and New Discontent in the Wake of Covid-19," CESifo Working Paper Series 10803, CESifo.
    • Handle: RePEc:ces:ceswps:_10803
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    File URL: https://www.cesifo.org/DocDL/cesifo1_wp10803.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Twitter; scepticism; public health; media; vaccines; Covid-19;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J28 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Safety; Job Satisfaction; Related Public Policy
    • J60 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media

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