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Using big data to understand the online ecology of COVID-19 vaccination hesitancy

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  • Shasha Teng

    (Taylor’s University)

  • Nan Jiang

    (Taylor’s University)

  • Kok Wei Khong

    (Taylor’s University)

Abstract

With a large population of people vaccinated, it is possible that at-risk people are shielded, and the coronavirus disease is contained. Given the low vaccine uptakes, achieving herd immunity via vaccination campaigns can be challenging. After a literature review, we found a paucity of research studies of vaccine hesitancy from social media settings. This study aims to categorise and create a typology of social media contents and assess the priority of concerns for future public health messaging. With a dataset of 43,203 YouTube comments, we applied text analytics and multiple regression analyses to examine the correlations between vaccine hesitancy factors and vaccination intention. Our major findings are (i) Polarized views on vaccines existed in the social media ecology of public discourse, with a majority of people unwilling to get vaccinated against COVID-19; (ii) Reasons behind vaccine hesitancy included concerns about vaccine safety, potential side-effects, lack of trust in government and pharmaceutical companies; (iii) Political partisan-preferences were exemplified in vaccine decision-making processes; (iv) Anti-vaccine movements with amplified misinformation fuelled vaccine hesitancy and undermined public confidence in COVID-19 vaccines. We suggest public health practitioners engage in social media and craft evidenced-based messages to online communities in a balanced and palatable way.

Suggested Citation

  • Shasha Teng & Nan Jiang & Kok Wei Khong, 2022. "Using big data to understand the online ecology of COVID-19 vaccination hesitancy," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-15, December.
    • Handle: RePEc:pal:palcom:v:9:y:2022:i:1:d:10.1057_s41599-022-01185-6
    DOI: 10.1057/s41599-022-01185-6
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    References listed on IDEAS

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    1. Romer, Daniel & Jamieson, Kathleen Hall, 2020. "Conspiracy theories as barriers to controlling the spread of COVID-19 in the U.S," Social Science & Medicine, Elsevier, vol. 263(C).
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    3. Sahil Loomba & Alexandre Figueiredo & Simon J. Piatek & Kristen Graaf & Heidi J. Larson, 2021. "Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA," Nature Human Behaviour, Nature, vol. 5(3), pages 337-348, March.
    4. Tali Sharot, 2021. "To quell misinformation, use carrots — not just sticks," Nature, Nature, vol. 591(7850), pages 347-347, March.
    5. Jamie Murphy & Frédérique Vallières & Richard P. Bentall & Mark Shevlin & Orla McBride & Todd K. Hartman & Ryan McKay & Kate Bennett & Liam Mason & Jilly Gibson-Miller & Liat Levita & Anton P. Martine, 2021. "Psychological characteristics associated with COVID-19 vaccine hesitancy and resistance in Ireland and the United Kingdom," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
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    Cited by:

    1. Prof. Sunny .E Udeze & Dr. Chidiebere Anthony Ezinwa & Dr. Ekwe Okwudiri, 2022. "Community Engagement: Perceptions and Responses to COVID-19 Risk Communication among Rural Dwellers in Enugu State," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 6(9), pages 708-717, September.
    2. Meng Cai & Han Luo & Xiao Meng & Ying Cui & Wei Wang, 2022. "Influence of information attributes on information dissemination in public health emergencies," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-22, December.

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