Background COVID-19 vaccines are considered one of the most effective ways for containing the COVID-19 pandemic, but Japan lagged behind other countries in vaccination in the early stages. A deeper understanding of the slow progress of vaccination in Japan can be instructive for COVID-19 booster vaccination and vaccinations during future pandemics. Objective This retrospective study aims to analyze the slow progress of early-stage vaccination in Japan by exploring opinions and sentiment toward the COVID-19 vaccine in Japanese tweets before and at the beginning of vaccination. Methods We collected 144,101 Japanese tweets containing COVID-19 vaccine-related keywords between August 1, 2020, and June 30, 2021. We visualized the trend of the tweets and sentiments and identified the critical events that may have triggered the surges. Correlations between sentiments and the daily infection, death, and vaccination cases were calculated. The latent dirichlet allocation model was applied to identify topics of negative tweets from the beginning of vaccination. We also conducted an analysis of vaccine brands (Pfizer, Moderna, AstraZeneca) approved in Japan. Results The daily number of tweets continued with accelerating growth after the start of large-scale vaccinations in Japan. The sentiments of around 85% of the tweets were neutral, and negative sentiment overwhelmed the positive sentiment in the other tweets. We identified 6 public-concerned topics related to the negative sentiment at the beginning of the vaccination process. Among the vaccines from the 3 manufacturers, the attitude toward Moderna was the most positive, and the attitude toward AstraZeneca was the most negative. Conclusions Negative sentiment toward vaccines dominated positive sentiment in Japan, and the concerns about side effects might have outweighed fears of infection at the beginning of the vaccination process. Topic modeling on negative tweets indicated that the government and policy makers should take prompt actions in building a safe and convenient vaccine reservation and rollout system, which requires both flexibility of the medical care system and the acceleration of digitalization in Japan. The public showed different attitudes toward vaccine brands. Policy makers should provide more evidence about the effectiveness and safety of vaccines and rebut fake news to build vaccine confidence.

Background: The global public health and socioeconomic impacts of COVID-19 have been substantial. To achieve herd immunity, widespread use of the vaccine is required, and it is therefore critical for government and public health agencies to understand public perceptions of the vaccine to help sustain subsequent vaccinations. Objective: This study aims to explore the opinions and sentiments of tweets about COVID-19 vaccination among Twitter users in Japan, both before and at the beginning of the COVID-19 vaccination program. Methods: We collected 144,101 Japanese tweets containing COVID-19 vaccine-related keywords from Japanese Twitter users between August 1, 2020, and June 30, 2021. Specifically, we identified temporal changes in the number of tweets and key events that triggered a surge in the number of tweets. In addition, we performed sentiment analysis, and calculated the correlation between different sentiments and the number of deaths, infections, and vaccinations. We also built latent Dirichlet allocation (LDA) topic models to identify commonly discussed topics in a large sample of tweets. We also provided a word cloud of high-frequency unigram and bigram tokens as additional evidence, and conducted further analysis on three different vaccine brands. Results: The overall number of tweets has continued to increase since the start of mass vaccination in Japan. Sentiments were generally neutral, but negative sentiment was more significant than positive sentiment. Before and after the first vaccination in Japan, the correlations of negative/positive sentiment with death, infection, and vaccination cases changed significantly. Public concerns revolved around three themes: information on vaccine reservations and vaccinations in Japan; infection and mutation of COVID-19 in Japan; and prevention measures, vaccine development and supply, and vaccination status in other countries. Furthermore, public attention to the three brands of vaccines has a temporal shift as clinical trials move forward. Conclusions: The number of tweets and changes in sentiment are primarily driven by major news events in relation to the COVID-19 vaccine, with negative sentiments dominating positive sentiments overall. Death and infection cases correlated significantly with negative sentiments, but the correlation fell after vaccinations began as morbidity and mortality decreased. The attention of the public to different vaccine brands had a temporal change during their clinical trial process, and although the discussion points are slightly different, the core remains effective and secure.

Background The global public health and socioeconomic impacts of the COVID-19 pandemic have been substantial, rendering herd immunity by COVID-19 vaccination an important factor for protecting people and retrieving the economy. Among all the countries, Japan became one of the countries with the highest COVID-19 vaccination rates in several months, although vaccine confidence in Japan is the lowest worldwide. Objective We attempted to find the reasons for rapid COVID-19 vaccination in Japan given its lowest vaccine confidence levels worldwide, through Twitter analysis.  Methods We downloaded COVID-19–related Japanese tweets from a large-scale public COVID-19 Twitter chatter data set within the timeline of February 1 and September 30, 2021. The daily number of vaccination cases was collected from the official website of the Prime Minister’s Office of Japan. After preprocessing, we applied unigram and bigram token analysis and then calculated the cross-correlation and Pearson correlation coefficient (r) between the term frequency and daily vaccination cases. We then identified vaccine sentiments and emotions of tweets and used the topic modeling to look deeper into the dominant emotions.  Results We selected 190,697 vaccine-related tweets after filtering. Through n-gram token analysis, we discovered the top unigrams and bigrams over the whole period. In all the combinations of the top 6 unigrams, tweets with both keywords “reserve” and “venue” showed the largest correlation with daily vaccination cases (r=0.912; P<.001). On sentiment analysis, negative sentiment overwhelmed positive sentiment, and fear was the dominant emotion across the period. For the latent Dirichlet allocation model on tweets with fear emotion, the two topics were identified as “infect” and “vaccine confidence.” The expectation of the number of tweets generated from topic “infect” was larger than that generated from topic “vaccine confidence.” Conclusions Our work indicates that awareness of the danger of COVID-19 might increase the willingness to get vaccinated. With a sufficient vaccine supply, effective delivery of vaccine reservation information may be an important factor for people to get vaccinated. We did not find evidence for increased vaccine confidence in Japan during the period of our study. We recommend policy makers to share accurate and prompt information about the infectious diseases and vaccination and to make efforts on smoother delivery of vaccine reservation information.

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BackgroundThe global public health and socioeconomic impacts of coronavirus disease 2019 (COVID-19) have been substantial, making herd immunity by COVID-19 vaccination an important factor for protecting people and retrieving the economy. Among all the countries, Japan became one of the countries with the highest COVID-19 vaccination rate in several months, although the vaccine confidence in Japan is the lowest worldwide.ObjectiveWe attempted to find the reasons for the rapid coronavirus disease 2019 (COVID-19) vaccination in Japan under the lowest vaccine confidence in the world by Twitter analysis.Materials and methodsWe downloaded COVID-19 related Japanese tweets from a large-scale public COVID-19 Twitter chatter dataset within the timeline of February 1, 2021 and September 30, 2021. The daily number of vaccination cases was collected from the official website of the Prime Minister’s Office of Japan. After preprocessing, we applied unigram and bigram token analysis, then calculated the cross correlation and Pearson correlation coefficient (r) between the term frequency and daily vaccination cases. Then we identified vaccine sentiments and emotions of tweets and used the topic modeling to look deeper into the dominant emotions.ResultsWe selected 190,697 vaccine-related tweets after filtering. By n-gram token analysis, we discovered the top unigrams and bigrams over the whole period. In all the combinations of the top six unigrams, tweets with both keywords “reserve” and “venue” showed the largest r = 0.912 (P < 0.001) with the daily vaccination cases. In sentiment analysis, negative sentiment overwhelmed positive sentiment, and fear was the dominant emotion across the period. For the latent Dirichlet allocation model on tweets with fear emotion, the two topics were identified as “infect” and “vaccine confidence”. The expectation of the number of tweets generated from topic “infect” was larger than “vaccine confidence.”ConclusionOur work indicated that awareness of the danger of COVID-19 might increase the willingness to get vaccinated; With sufficient vaccine supply, effective vaccine reservation information delivery may be an important factor for people to get vaccinated; We didn’t find evidence for increased vaccine confidence in Japan during the period in our research. We recommend policymakers to share fair and prompt information about the infectious diseases and vaccination, and make efforts on smoother delivery of vaccine-reservation information.