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

Infodemiology and Infoveillance (1360) JMIR Theme Issue: COVID-19 Special Issue (2457) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1048) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1656) Infectious Diseases (non-STD/STI) (1584) Mass Media/Social Media Communication and Campaigns (466) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1519) Outbreak and Pandemic Preparedness and Management (1737) Discourse (38)

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 Jang1, 2 Author Orcid Image ;   Emily Rempel2 Author Orcid Image ;   David Roth2 Author Orcid Image ;   Giuseppe Carenini1 Author Orcid Image ;   Naveed Zafar Janjua2, 3, 4 Author Orcid Image
Article Authors Cited by (100) Tweetations (9) Metrics

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