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) Infodemiology and Infoveillance (1369) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Natural Language Processing (708) Outbreak and Pandemic Preparedness and Management (1743) Infectious Diseases (non-STD/STI) (1594) Machine Learning (1505) Quality/Credibility of eHealth Information and Trust Issues (544) Information Quality in Digital Media (347)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26302, first published .
Using Tweets to Understand How COVID-19–Related Health Beliefs Are Affected in the Age of Social Media: Twitter Data Analysis Study

Using Tweets to Understand How COVID-19–Related Health Beliefs Are Affected in the Age of Social Media: Twitter Data Analysis Study

Using Tweets to Understand How COVID-19–Related Health Beliefs Are Affected in the Age of Social Media: Twitter Data Analysis Study

Authors of this article:

Hanyin Wang1 Author Orcid Image ;   Yikuan Li1 Author Orcid Image ;   Meghan Hutch1 Author Orcid Image ;   Andrew Naidech2 Author Orcid Image ;   Yuan Luo1 Author Orcid Image
Article Authors Cited by (36) Tweetations (26) Metrics

Hanyin Wang   1 , BMed ;   Yikuan Li   1 , BSc, MSc ;   Meghan Hutch   1 , BSc ;   Andrew Naidech   2 , MD, MSPH ;   Yuan Luo   1 , PhD

1 Department of Preventive Medicine, Northwestern University, Chicago, IL, United States

2 Department of Neurology, Northwestern Universtity, Chicago, IL, United States

Corresponding Author: