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

Theme Issue 2022: The Present and Future of Pandemic Technologies (11) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Information Quality in Digital Media (340) Infodemiology and Infoveillance (1349) Quality/Credibility of eHealth Information and Trust Issues (531) Wikis (16)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45024, first published .
Crowdsourcing Knowledge Production of COVID-19 Information on Japanese Wikipedia in the Face of Uncertainty: Empirical Analysis

Crowdsourcing Knowledge Production of COVID-19 Information on Japanese Wikipedia in the Face of Uncertainty: Empirical Analysis

Crowdsourcing Knowledge Production of COVID-19 Information on Japanese Wikipedia in the Face of Uncertainty: Empirical Analysis

Authors of this article:

Kunhao Yang1 Author Orcid Image ;   Mikihito Tanaka2 Author Orcid Image
Article Authors Cited by (1) Tweetations (54) Metrics

Kunhao Yang   1 , PhD ;   Mikihito Tanaka   2 , PhD

1 Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Ube, Japan

2 Faculty of Political Science and Economics, Waseda University, Tokyo, Japan

Corresponding Author:

  • Kunhao Yang, PhD
  • Graduate School of Sciences and Technology for Innovation
  • Yamaguchi University
  • 2-16-1 Tokiwa-dai
  • Ube, 755-8611
  • Japan
  • Phone: 81 07038477887
  • Email: yangkunhao93@gmail.com