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

Infoveillance and Social Listening (254) JMIR Theme Issue: COVID-19 Special Issue (2498) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1793) Infodemiology and Infoveillance (1461) Outbreak and Pandemic Preparedness and Management (1782) Early Results from COVID-19 Studies (338) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1089)

Published on in Vol 4 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37881, first published .
Verification in the Early Stages of the COVID-19 Pandemic: Sentiment Analysis of Japanese Twitter Users

Verification in the Early Stages of the COVID-19 Pandemic: Sentiment Analysis of Japanese Twitter Users

Verification in the Early Stages of the COVID-19 Pandemic: Sentiment Analysis of Japanese Twitter Users

Authors of this article:

Ryuichiro Ueda1 Author Orcid Image ;   Feng Han2 Author Orcid Image ;   Hongjian Zhang1 Author Orcid Image ;   Tomohiro Aoki1 Author Orcid Image ;   Katsuhiko Ogasawara1 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Biliotti C, Fraccaroli N, Puliga M, Bargagli-Stoffi F, Riccaboni M. The Impact of Stay-At-Home Mandates on Uncertainty and Sentiments: Quasi-Experimental Study. Journal of Medical Internet Research 2025;27:e64667 View
  2. Kalia P, Kaur M, Thomas A. E‐Tailers' Twitter (X) Communication: A Textual Analysis. International Journal of Consumer Studies 2025;49(3) View