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

Infodemiology and Infoveillance (1349) Public (e)Health, Digital Epidemiology and Public Health Informatics (725) Outbreak and Pandemic Preparedness and Management (1727) Vaccination and Immunization in the Digital Age (374) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infectious Diseases (non-STD/STI) (1575) Early Results from COVID-19 Studies (299)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49753, first published .
Deep Learning Analysis of COVID-19 Vaccine Hesitancy and Confidence Expressed on Twitter in 6 High-Income Countries: Longitudinal Observational Study

Deep Learning Analysis of COVID-19 Vaccine Hesitancy and Confidence Expressed on Twitter in 6 High-Income Countries: Longitudinal Observational Study

Deep Learning Analysis of COVID-19 Vaccine Hesitancy and Confidence Expressed on Twitter in 6 High-Income Countries: Longitudinal Observational Study

Authors of this article:

Xinyu Zhou1, 2, 3 Author Orcid Image ;   Suhang Song4 Author Orcid Image ;   Ying Zhang1, 2 Author Orcid Image ;   Zhiyuan Hou1, 2 Author Orcid Image
Article Authors Cited by (3) Tweetations (11) Metrics

Xinyu Zhou   1, 2, 3 * , BS ;   Suhang Song   4 * , PhD ;   Ying Zhang   1, 2 , BS ;   Zhiyuan Hou   1, 2 , PhD

1 School of Public Health, Fudan University, Shanghai, China

2 Global Health Institute, Fudan University, Shanghai, China

3 Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States

4 Department of Health Policy and Management, College of Public Health, University of Georgia, Athens, GA, United States

*these authors contributed equally

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