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

Infoveillance and Social Listening (216) JMIR Theme Issue: COVID-19 Special Issue (2465) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1053) Infodemiology and Infoveillance (1379) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1681) Machine Learning (1524)

Published on in Vol 2, No 2 (2022): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37861, first published .
COVID-19 Health Beliefs Regarding Mask Wearing and Vaccinations on Twitter: Deep Learning Approach

COVID-19 Health Beliefs Regarding Mask Wearing and Vaccinations on Twitter: Deep Learning Approach

COVID-19 Health Beliefs Regarding Mask Wearing and Vaccinations on Twitter: Deep Learning Approach

Authors of this article:

Si Yang Ke1 Author Orcid Image ;   E Shannon Neeley-Tass1 Author Orcid Image ;   Michael Barnes2 Author Orcid Image ;   Carl L Hanson2 Author Orcid Image ;   Christophe Giraud-Carrier3 Author Orcid Image ;   Quinn Snell3 Author Orcid Image
Article Authors Cited by Tweetations (3) Metrics

Si Yang Ke   1 * , BS ;   E Shannon Neeley-Tass   1 * , PhD ;   Michael Barnes   2 * , PhD ;   Carl L Hanson   2 * , PhD ;   Christophe Giraud-Carrier   3 * , PhD ;   Quinn Snell   3 * , PhD

1 Department of Statistics, Brigham Young University, Provo, UT, United States

2 Department of Public Health, Brigham Young University, Provo, UT, United States

3 Computer Science Department, Brigham Young University, Provo, UT, United States

*all authors contributed equally

Corresponding Author:

  • Quinn Snell, PhD
  • Computer Science Department
  • Brigham Young University
  • 3361 TMCB
  • Provo, UT, 84602
  • United States
  • Phone: 1 801-422-5098
  • Email: snell@cs.byu.edu