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

JMIR Theme Issue: COVID-19 Special Issue (2391) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1569) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1013) Mass Media/Social Media Communication and Campaigns (448) Infodemiology and Infoveillance (1273)

Published on in Vol 24, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40160, first published .
Using Natural Language Processing to Explore “Dry January” Posts on Twitter: Longitudinal Infodemiology Study

Using Natural Language Processing to Explore “Dry January” Posts on Twitter: Longitudinal Infodemiology Study

Using Natural Language Processing to Explore “Dry January” Posts on Twitter: Longitudinal Infodemiology Study

Authors of this article:

Alex M Russell1 Author Orcid Image ;   Danny Valdez2 Author Orcid Image ;   Shawn C Chiang1 Author Orcid Image ;   Ben N Montemayor3 Author Orcid Image ;   Adam E Barry3 Author Orcid Image ;   Hsien-Chang Lin2 Author Orcid Image ;   Philip M Massey1 Author Orcid Image
Article Authors Cited by (5) Tweetations (5) Metrics

Alex M Russell   1 , PhD ;   Danny Valdez   2 , PhD ;   Shawn C Chiang   1 , MPH ;   Ben N Montemayor   3 , PhD ;   Adam E Barry   3 , PhD ;   Hsien-Chang Lin   2 , PhD ;   Philip M Massey   1 , PhD

1 Center for Public Health and Technology, Department of Health, Human Performance, and Recreation, University of Arkansas, Fayetteville, AR, United States

2 Department of Applied Health Science, School of Public Health, Indiana University, Bloomington, IN, United States

3 Department of Health and Kinesiology, Texas A&M University, College Station, TX, United States

Corresponding Author:

  • Alex M Russell, PhD
  • Center for Public Health and Technology
  • Department of Health, Human Performance, and Recreation
  • University of Arkansas
  • HPER Building, 308-V
  • Fayetteville, AR, 72701
  • United States
  • Phone: 1 479-575-8672
  • Email: ar117@uark.edu