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

JMIR Theme Issue: COVID-19 Special Issue (2452) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Outbreak and Pandemic Preparedness and Management (1727) Quality/Credibility of eHealth Information and Trust Issues (531) Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infectious Diseases (non-STD/STI) (1575) Information Quality in Digital Media (340) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Mass Media/Social Media Communication and Campaigns (461) Machine Learning (1465)

Published on in Vol 23, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23957, first published .
Public Opinions and Concerns Regarding the Canadian Prime Minister’s Daily COVID-19 Briefing: Longitudinal Study of YouTube Comments Using Machine Learning Techniques

Public Opinions and Concerns Regarding the Canadian Prime Minister’s Daily COVID-19 Briefing: Longitudinal Study of YouTube Comments Using Machine Learning Techniques

Public Opinions and Concerns Regarding the Canadian Prime Minister’s Daily COVID-19 Briefing: Longitudinal Study of YouTube Comments Using Machine Learning Techniques

Authors of this article:

Chengda Zheng1 Author Orcid Image ;   Jia Xue1, 2 Author Orcid Image ;   Yumin Sun1 Author Orcid Image ;   Tingshao Zhu3, 4 Author Orcid Image
Article Authors Cited by (9) Tweetations (9) Metrics

Chengda Zheng   1 * , BSc ;   Jia Xue   1, 2 * , PhD ;   Yumin Sun   1 , BSc ;   Tingshao Zhu   3, 4 , PhD

1 Faculty of Information, University of Toronto, Toronto, ON, Canada

2 Factor Inwentash Faculty of Social Work, University of Toronto, Toronto, ON, Canada

3 Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China

4 Department of Psychology, University of Chinese Academy of Sciences, Beijing, China

*these authors contributed equally

Corresponding Author:

  • Tingshao Zhu, PhD
  • Key Laboratory of Behavioral Science
  • Institute of Psychology
  • Chinese Academy of Sciences
  • 16 Lincui Road, Chaoyang district
  • Beijing, 100101
  • China
  • Phone: 86 1064871661
  • Email: tszhu@psych.ac.cn