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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - COVID-19 vaccine conspiracy theories, discourses of liberty, and “the new normal” on social media
AU - McGlashan, Mark
AU - Clarke, Isobelle
AU - Gee, Matt
AU - Grieshofer, Tatiana
AU - Kehoe, Andrew
AU - Lawson, Robert
PY - 2025/3/11
Y1 - 2025/3/11
N2 - Public distrust in government, pharmaceutical companies, healthcare professions, and medical science and technology has been consistently linked with vaccine rejection. Policymakers, therefore, want to better understand links between distrust of institutions and vaccine refusal. This paper reports on a case study of posts (tweets) to the social media platform Twitter (now X) collected as part of the TRAC:COVID (Trust and Communication: A Coronavirus Online Visual Dashboard) project. The TRAC:COVID dashboard combines methods from corpus linguistics with various visualization techniques to enable users to explore approximately 84 million posts containing reference to COVID-19 published between 1 January 2020 and 30 April 2021 (encompassing the dates of UK coronavirus lockdowns). The dashboard and all sampling considerations (including an overview of the detailed search query used) are available at https://www.traccovid.com. Specifically, the paper analyses a subsample of posts that make reference to vaccines and contain at least one hashtag relating to various categories of dis/misinformation. By employing keyword co-occurrence analysis – a method for examining statistically significant keywords using multiple correspondence analysis – we find that these posts draw on various “discourses of liberty” to protest against perceived infringements on “health freedoms” through the imposition of new norms of behaviour (e.g., mask-wearing).
AB - Public distrust in government, pharmaceutical companies, healthcare professions, and medical science and technology has been consistently linked with vaccine rejection. Policymakers, therefore, want to better understand links between distrust of institutions and vaccine refusal. This paper reports on a case study of posts (tweets) to the social media platform Twitter (now X) collected as part of the TRAC:COVID (Trust and Communication: A Coronavirus Online Visual Dashboard) project. The TRAC:COVID dashboard combines methods from corpus linguistics with various visualization techniques to enable users to explore approximately 84 million posts containing reference to COVID-19 published between 1 January 2020 and 30 April 2021 (encompassing the dates of UK coronavirus lockdowns). The dashboard and all sampling considerations (including an overview of the detailed search query used) are available at https://www.traccovid.com. Specifically, the paper analyses a subsample of posts that make reference to vaccines and contain at least one hashtag relating to various categories of dis/misinformation. By employing keyword co-occurrence analysis – a method for examining statistically significant keywords using multiple correspondence analysis – we find that these posts draw on various “discourses of liberty” to protest against perceived infringements on “health freedoms” through the imposition of new norms of behaviour (e.g., mask-wearing).
U2 - 10.1515/lingvan-2024-0121
DO - 10.1515/lingvan-2024-0121
M3 - Journal article
JO - Linguistics Vanguard
JF - Linguistics Vanguard
SN - 2199-174X
ER -