COVID-19 Vaccine Hesitancy: Analysing Twitter to Identify Barriers to Vaccination in a Low Uptake Region of the UK
This case study explored the value of soft-intelligence, leveraged using AI, as an evidence source to support public health research. A natural language processing platform rapidly identified and analyzed key barriers to vaccine uptake from a collection of geo-located tweets from London, UK. Over 90,000 tweets were captured between November 30, 2020 and August 15, 2021, and the platform’s algorithm clustered them according to their topic and sentiment, from which 900+ tweets were extracted from the top 12 negative sentiment topic clusters. Results report that people did not get vaccinated out of concerns for safety, mistrust of the government and pharmaceutical companies and accessibility issues. Misinformation was widely spread among Twitter users, and the government is encouraged to think differently about vaccination campaigns.
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