Abstract
The current study aimed to explore the public understanding of COVID-19 vaccines and the social representations emerging from a corpus of user-generated comments on YouTube videos posted during the year following the World Health Organization's declaration of the novel coronavirus as pandemic. We used Structural Topic Modelling to process the text and identified a 10-topic solution as the best to represent the corpus of text data. The exploration of the topics showed a complex landscape of social representations underlying a plurality of perspectives, which we interpreted as reflecting different users’ needs to make sense of the unprecedented events. Implications for theory, future research, and intervention for health psychology and policy are discussed.
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