This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2452) Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641)

Published on in Vol 24, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41928, first published .
Evolution of Public Opinion on COVID-19 Vaccination in Japan: Large-Scale Twitter Data Analysis

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

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

Authors of this article:

Ryota Kobayashi1, 2, 3 Author Orcid Image ;   Yuka Takedomi4 Author Orcid Image ;   Yuri Nakayama1 Author Orcid Image ;   Towa Suda4 Author Orcid Image ;   Takeaki Uno4 Author Orcid Image ;   Takako Hashimoto5 Author Orcid Image ;   Masashi Toyoda6 Author Orcid Image ;   Naoki Yoshinaga6 Author Orcid Image ;   Masaru Kitsuregawa6, 7 Author Orcid Image ;   Luis E C Rocha8, 9 Author Orcid Image
Article Authors Cited by (8) Tweetations (18) Metrics

Journals

  1. Cheng T, Han B, Liu Y. Exploring public sentiment and vaccination uptake of COVID-19 vaccines in England: a spatiotemporal and sociodemographic analysis of Twitter data. Frontiers in Public Health 2023;11 View
  2. Lotto M, Zakir Hussain I, Kaur J, Butt Z, Cruvinel T, Morita P. Analysis of Fluoride-Free Content on Twitter: Topic Modeling Study. Journal of Medical Internet Research 2023;25:e44586 View
  3. Goto A, Satoh K, Reich M. Two pills and women’s health in Japan. The Lancet Regional Health - Western Pacific 2023;40:100946 View
  4. Valeanu A, Mihai D, Andrei C, Puscasu C, Ionica A, Hinoveanu M, Predoi V, Bulancea E, Chirita C, Negres S, Marineci C. Identification, analysis and prediction of valid and false information related to vaccines from Romanian tweets. Frontiers in Public Health 2024;12 View
  5. Paoletti G, Dall’Amico L, Kalimeri K, Lenti J, Mejova Y, Paolotti D, Starnini M, Tizzani M. Political context of the European vaccine debate on Twitter. Scientific Reports 2024;14(1) View
  6. De Clerck B, Fernandez Toledano J, Van Utterbeeck F, Rocha L. Detecting coordinated and bot-like behavior in Twitter: the Jürgen Conings case. EPJ Data Science 2024;13(1) View
  7. Liu Z, Wu J, Wu C, Xia X. Shifting sentiments: analyzing public reaction to COVID-19 containment policies in Wuhan and Shanghai through Weibo data. Humanities and Social Sciences Communications 2024;11(1) View
  8. Takedomi Y, Nakayama Y, Suda T, Uno T, Hashimoto T, Toyoda M, Yoshinaga N, Kitsuregawa M, Kobayashi R. Evolution of COVID-19 Vaccination-related Topics on Twitter. Transactions of the Japanese Society for Artificial Intelligence 2024;39(5):C-N93_1 View