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

Infodemiology and Infoveillance (966) JMIR Theme Issue: COVID-19 Special Issue (1993) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (784) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1225) Infectious Diseases (non-STD/STI) (1198) Mass Media/Social Media Communication and Campaigns (394) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1296) Outbreak and Pandemic Preparedness and Management (1392)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25431, first published .
Tracking COVID-19 Discourse on Twitter in North America: Infodemiology Study Using Topic Modeling and Aspect-Based Sentiment Analysis

Tracking COVID-19 Discourse on Twitter in North America: Infodemiology Study Using Topic Modeling and Aspect-Based Sentiment Analysis

Tracking COVID-19 Discourse on Twitter in North America: Infodemiology Study Using Topic Modeling and Aspect-Based Sentiment Analysis

Authors of this article:

Hyeju Jang 1, 2 Author Orcid Image ;   Emily Rempel 2 Author Orcid Image ;   David Roth 2 Author Orcid Image ;   Giuseppe Carenini 1 Author Orcid Image ;   Naveed Zafar Janjua 2, 3, 4 Author Orcid Image
Article Authors Cited by (8) Tweetations (9) Metrics
Hyeju Jang 1, 2 , MSc, PhD ;   Emily Rempel 2 , MSc, PhD ;   David Roth 2 , MSc, PhD ;   Giuseppe Carenini 1 , MSc, PhD ;   Naveed Zafar Janjua 2, 3, 4 , MBBS, MSc, DrPH

1 Department of Computer Science , University of British Columbia , Vancouver , BC , CA

2 British Columbia Centre for Disease Control , Vancouver , BC , CA

3 School of Population and Public Health , University of British Columbia , Vancouver , BC , CA

4 Centre for Health Evaluation and Outcome Sciences , University of British Columbia , Vancouver , BC , CA

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