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How epidemic psychology works on Twitter: evolution of responses to the COVID-19 pandemic in the U.S

Author

Listed:
  • Luca Maria Aiello

    (Nokia Bell Labs
    IT University)

  • Daniele Quercia

    (Nokia Bell Labs
    King’s College London)

  • Ke Zhou

    (Nokia Bell Labs)

  • Marios Constantinides

    (Nokia Bell Labs)

  • Sanja Šćepanović

    (Nokia Bell Labs)

  • Sagar Joglekar

    (Nokia Bell Labs)

Abstract

Disruptions resulting from an epidemic might often appear to amount to chaos but, in reality, can be understood in a systematic way through the lens of “epidemic psychology”. According to Philip Strong, the founder of the sociological study of epidemic infectious diseases, not only is an epidemic biological; there is also the potential for three psycho-social epidemics: of fear, moralization, and action. This work empirically tests Strong’s model at scale by studying the use of language of 122M tweets related to the COVID-19 pandemic posted in the U.S. during the whole year of 2020. On Twitter, we identified three distinct phases. Each of them is characterized by different regimes of the three psycho-social epidemics. In the refusal phase, users refused to accept reality despite the increasing number of deaths in other countries. In the anger phase (started after the announcement of the first death in the country), users’ fear translated into anger about the looming feeling that things were about to change. Finally, in the acceptance phase, which began after the authorities imposed physical-distancing measures, users settled into a “new normal” for their daily activities. Overall, refusal of accepting reality gradually died off as the year went on, while acceptance increasingly took hold. During 2020, as cases surged in waves, so did anger, re-emerging cyclically at each wave. Our real-time operationalization of Strong’s model is designed in a way that makes it possible to embed epidemic psychology into real-time models (e.g., epidemiological and mobility models).

Suggested Citation

  • Luca Maria Aiello & Daniele Quercia & Ke Zhou & Marios Constantinides & Sanja Šćepanović & Sagar Joglekar, 2021. "How epidemic psychology works on Twitter: evolution of responses to the COVID-19 pandemic in the U.S," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-15, December.
  • Handle: RePEc:pal:palcom:v:8:y:2021:i:1:d:10.1057_s41599-021-00861-3
    DOI: 10.1057/s41599-021-00861-3
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    References listed on IDEAS

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    1. Thiemo Fetzer & Lukas Hensel & Johannes Hermle & Christopher Roth, 2021. "Coronavirus Perceptions and Economic Anxiety," The Review of Economics and Statistics, MIT Press, vol. 103(5), pages 968–978-9, December.
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    4. Ana I. Bento & Thuy Nguyen & Coady Wing & Felipe Lozano-Rojas & Yong-Yeol Ahn & Kosali Simon, 2020. "Evidence from internet search data shows information-seeking responses to news of local COVID-19 cases," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(21), pages 11220-11222, May.
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    Cited by:

    1. Mario Bisiada, 2021. "Discursive structures and power relations in Covid-19 knowledge production," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-10, December.
    2. Katarzyna Kotlarska & Benita Wielgus & Łukasz Cichocki, 2021. "Phenomenology of the COVID-19 Pandemic Experience in Patients Suffering from Chronic Schizophrenia—A Qualitative Analysis," IJERPH, MDPI, vol. 19(1), pages 1-12, December.

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