Evolution of Public Opinion on COVID-19 Vaccination in Japan: Large-Scale Twitter Data Analysis

BackgroundVaccines are promising tools to control the spread of COVID-19. An effective vaccination campaign requires government policies and community engagement, sharing experiences for social support, and voicing concerns about vaccine safety and efficiency. The increasing use of online social pla...

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Main Authors: Ryota Kobayashi (Author), Yuka Takedomi (Author), Yuri Nakayama (Author), Towa Suda (Author), Takeaki Uno (Author), Takako Hashimoto (Author), Masashi Toyoda (Author), Naoki Yoshinaga (Author), Masaru Kitsuregawa (Author), Luis E C Rocha (Author)
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Published: JMIR Publications, 2022-12-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Ryota Kobayashi  |e author 
700 1 0 |a Yuka Takedomi  |e author 
700 1 0 |a Yuri Nakayama  |e author 
700 1 0 |a Towa Suda  |e author 
700 1 0 |a Takeaki Uno  |e author 
700 1 0 |a Takako Hashimoto  |e author 
700 1 0 |a Masashi Toyoda  |e author 
700 1 0 |a Naoki Yoshinaga  |e author 
700 1 0 |a Masaru Kitsuregawa  |e author 
700 1 0 |a Luis E C Rocha  |e author 
245 0 0 |a Evolution of Public Opinion on COVID-19 Vaccination in Japan: Large-Scale Twitter Data Analysis 
260 |b JMIR Publications,   |c 2022-12-01T00:00:00Z. 
500 |a 1438-8871 
500 |a 10.2196/41928 
520 |a BackgroundVaccines are promising tools to control the spread of COVID-19. An effective vaccination campaign requires government policies and community engagement, sharing experiences for social support, and voicing concerns about vaccine safety and efficiency. The increasing use of online social platforms allows us to trace large-scale communication and infer public opinion in real time. ObjectiveThis study aimed to identify the main themes in COVID-19 vaccine-related discussions on Twitter in Japan and track how the popularity of the tweeted themes evolved during the vaccination campaign. Furthermore, we aimed to understand the impact of critical social events on the popularity of the themes. MethodsWe collected more than 100 million vaccine-related tweets written in Japanese and posted by 8 million users (approximately 6.4% of the Japanese population) from January 1 to October 31, 2021. We used Latent Dirichlet Allocation to perform automated topic modeling of tweet text during the vaccination campaign. In addition, we performed an interrupted time series regression analysis to evaluate the impact of 4 critical social events on public opinion. ResultsWe identified 15 topics grouped into the following 4 themes: (1) personal issue, (2) breaking news, (3) politics, and (4) conspiracy and humor. The evolution of the popularity of themes revealed a shift in public opinion, with initial sharing of attention over personal issues (individual aspect), collecting information from news (knowledge acquisition), and government criticism to focusing on personal issues. Our analysis showed that the Tokyo Olympic Games affected public opinion more than other critical events but not the course of vaccination. Public opinion about politics was significantly affected by various social events, positively shifting attention in the early stages of the vaccination campaign and negatively shifting attention later. ConclusionsThis study showed a striking shift in public interest in Japan, with users splitting their attention over various themes early in the vaccination campaign and then focusing only on personal issues, as trust in vaccines and policies increased. An interrupted time series regression analysis showed that the vaccination rollout to the general population (under 65 years) increased the popularity of tweets about practical advice and personal vaccination experience, and the Tokyo Olympic Games disrupted public opinion but not the course of the vaccination campaign. The methodology developed here allowed us to monitor the evolution of public opinion and evaluate the impact of social events on public opinion, using large-scale Twitter data. 
546 |a EN 
690 |a Computer applications to medicine. Medical informatics 
690 |a R858-859.7 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n Journal of Medical Internet Research, Vol 24, Iss 12, p e41928 (2022) 
787 0 |n https://www.jmir.org/2022/12/e41928 
787 0 |n https://doaj.org/toc/1438-8871 
856 4 1 |u https://doaj.org/article/ba2f85edb5c04b38b24573653bcf744b  |z Connect to this object online.