Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

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

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:

COVID-19 vaccines are considered one of the most effective ways for containing the COVID-19 pandemic, but Japan lagged 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:

144,101 Japanese tweets containing COVID-19 vaccine-related keywords were collected 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% tweets were neutral, and negative sentiment overwhelmed the positive sentiment in the other tweets. Six public-concerned topics were identified related to the negative sentiment at the beginning of the vaccination process. Among the vaccines of the three manufacturers, the attitude toward Moderna was the most positive and AstraZeneca 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 policymakers should take prompt actions in building a safe and convenient vaccine reservation and roll-out 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. Policymakers should provide more evidence about the effectiveness and safety of vaccines and rebut fake news to build vaccine confidence.


 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

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.