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Accepted for/Published in: JMIR Infodemiology

Date Submitted: Jul 23, 2021
Date Accepted: Apr 19, 2022

The final, peer-reviewed published version of this preprint can be found here:

Public Opinion and Sentiment Before and at the Beginning of COVID-19 Vaccinations in Japan: Twitter Analysis

Niu Q, Liu J, Kato M, Shinohara Y, Matsumura N, Aoyama T, Nagai-Tanima M

Public Opinion and Sentiment Before and at the Beginning of COVID-19 Vaccinations in Japan: Twitter Analysis

JMIR Infodemiology 2022;2(1):e32335

DOI: 10.2196/32335

PMID: 35578643

PMCID: 9092950

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Public Opinion and Sentiment Before and at the Beginning of COVID-19 Vaccinations in Japan: Twitter Analysis

  • Qian Niu; 
  • Junyu Liu; 
  • Masaya Kato; 
  • Yuki Shinohara; 
  • Natsuki Matsumura; 
  • Tomoki Aoyama; 
  • Momoko Nagai-Tanima

ABSTRACT

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 might be 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 public’s attention 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.


 Citation

Please cite as:

Niu Q, Liu J, Kato M, Shinohara Y, Matsumura N, Aoyama T, Nagai-Tanima M

Public Opinion and Sentiment Before and at the Beginning of COVID-19 Vaccinations in Japan: Twitter Analysis

JMIR Infodemiology 2022;2(1):e32335

DOI: 10.2196/32335

PMID: 35578643

PMCID: 9092950

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