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Long-term assessment of social amplification of risk during COVID-19: challenges to public health agencies amid misinformation and vaccine stance

Author

Listed:
  • Ali Unlu

    (Finnish Institute for Health and Welfare (THL)
    Aalto University)

  • Sophie Truong

    (Aalto University)

  • Nitin Sawhney

    (Aalto University)

  • Jonas Sivelä

    (Finnish Institute for Health and Welfare (THL))

  • Tuukka Tammi

    (Finnish Institute for Health and Welfare (THL))

Abstract

This study employs the Social Amplification of Risk Framework to investigate the stance on COVID-19 vaccines and the spread of misinformation on Twitter in Finland. Analyzing over 1.6 million tweets and manually annotating 4150 samples, the research highlights the challenges faced by the Finnish Institute for Health and Welfare (THL) in steering online vaccination communication. Using BERT models, Botometer, and additional computational methods, the study classifies text, identifies bot-like accounts, and detects malicious bots. Social network analysis further uncovers the underlying social structures and key actors in Twitter discussions during the pandemic. The THL remained a primary source of COVID-19 information throughout the pandemic, maintaining its influence despite challenges posed by malicious bots spreading misinformation and adopting negative vaccine stances. However, THL ceased its Twitter activity at the end of 2022 because its posts were being exploited to gain visibility and traction for misinformation and negative vaccine stance. The study also identifies key influencers in online vaccine discussions, suggesting avenues for improving public health communication. Overall, the research underscores the need to understand social media dynamics to counter misinformation and foster accurate public communication on COVID-19 and vaccination.

Suggested Citation

  • Ali Unlu & Sophie Truong & Nitin Sawhney & Jonas Sivelä & Tuukka Tammi, 2024. "Long-term assessment of social amplification of risk during COVID-19: challenges to public health agencies amid misinformation and vaccine stance," Journal of Computational Social Science, Springer, vol. 7(1), pages 809-836, April.
    • Handle: RePEc:spr:jcsosc:v:7:y:2024:i:1:d:10.1007_s42001-024-00257-8
    DOI: 10.1007/s42001-024-00257-8
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    References listed on IDEAS

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