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Vaccines are promising tools to control the spread of COVID-19. An effectivevaccination campaign requires government policies and community engagement,sharing experiences for social support, and voicing concerns to vaccine safetyand efficiency. The increasing use of online social platforms allows us totrace large-scale communication and infer public opinion in real-time. Wecollected more than 100 million vaccine-related tweets posted by 8 millionusers and used the Latent Dirichlet Allocation model to perform automated topicmodeling of tweet texts during the vaccination campaign in Japan. We identified15 topics grouped into 4 themes on Personal issue, Breaking news, Politics, andConspiracy and humour. The evolution of the popularity of themes revealed ashift in public opinion, initially sharing the attention over personal issues(individual aspect), collecting information from the news (knowledgeacquisition), and government criticisms, towards personal experiences onceconfidence in the vaccination campaign was established. An interrupted timeseries regression analysis showed that the Tokyo Olympic Games affected publicopinion more than other critical events but not the course of the vaccination.Public opinion on politics was significantly affected by various events,positively shifting the attention in the early stages of the vaccinationcampaign and negatively later. Tweets about personal issues were mostlyretweeted when the vaccination reached the younger population. The associationsbetween the vaccination campaign stages and tweet themes suggest that thepublic engagement in the social platform contributed to speedup vaccine uptakeby reducing anxiety via social learning and support.

Evolution of the public opinion on COVID-19 vaccination in Japan