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

JMIR Theme Issue: COVID-19 Special Issue (2461) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1667) Machine Learning (1505) Hygiene and Infection Prevention (326) Infectious Diseases (non-STD/STI) (1594) Outbreak and Pandemic Preparedness and Management (1743) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520)

Published on in Vol 22, No 9 (2020): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21419, first published .
Public Perceptions and Attitudes Toward COVID-19 Nonpharmaceutical Interventions Across Six Countries: A Topic Modeling Analysis of Twitter Data

Public Perceptions and Attitudes Toward COVID-19 Nonpharmaceutical Interventions Across Six Countries: A Topic Modeling Analysis of Twitter Data

Public Perceptions and Attitudes Toward COVID-19 Nonpharmaceutical Interventions Across Six Countries: A Topic Modeling Analysis of Twitter Data

Authors of this article:

Caitlin Doogan1, 2 Author Orcid Image ;   Wray Buntine2 Author Orcid Image ;   Henry Linger1 Author Orcid Image ;   Samantha Brunt3 Author Orcid Image
Article Authors Cited by (68) Tweetations (13) Metrics

Caitlin Doogan   1, 2 , MDataSci ;   Wray Buntine   2 , PhD ;   Henry Linger   1 , PhD ;   Samantha Brunt   3 , MD

1 Department of Human Centred Computing, Faculty of Information Technology, Monash University, Caulfield, Australia

2 Department of Data Science and AI, Faculty of Information Technology, Monash University, Clayton, Australia

3 Royal Perth Hospital, Perth, Australia

Corresponding Author:

  • Caitlin Doogan, MDataSci
  • Department of Data Science and AI
  • Faculty of Information Technology
  • Monash University
  • Wellington Rd
  • Clayton, 3800
  • Australia
  • Phone: 61 3 9903 1004
  • Email: caitlin.doogan@monash.edu