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

Peer-to-Peer Support and Online Communities (797) JMIR Theme Issue: COVID-19 Special Issue (2554) Infodemiology and Infoveillance (1558) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1139) Infoveillance and Social Listening (313)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67968, first published .
Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis

Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis

Exploring Conceptualizations of COVID-19 Risk in Ideologically Distinct Online Communities: A Computational Grounded Theory Analysis

Authors of this article:

Tiwaladeoluwa B Adekunle1 Author Orcid Image ;   Jeremy Foote2 Author Orcid Image ;   Toluwani E Adekunle3 Author Orcid Image ;   Nathan TeBlunthuis4 Author Orcid Image ;   Laura K Nelson5 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Tiwaladeoluwa B Adekunle   1 , BA, MA, PhD ;   Jeremy Foote   2 , PhD ;   Toluwani E Adekunle   3 , PhD ;   Nathan TeBlunthuis   4 , PhD ;   Laura K Nelson   5 , PhD

1 Feinberg School of Medicine, Northwestern University, Chicago, IL, United States

2 Purdue University, West Lafayette, IN, United States

3 Calvin University, Grand Rapids, MI, United States

4 University of Texas, Austin, TX, United States

5 University of British Columbia, Vancouver, BC, Canada

Corresponding Author: