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

Infoveillance and Social Listening (273) JMIR Theme Issue: COVID-19 Special Issue (2515) Natural Language Processing (836) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1826) Substance Abuse (491) Demographics of Users, Social & Digital Divide (862) Public Health Policy (75) Artificial Intelligence (1861) Information Demand (40)

Published on in Vol 5 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67333, first published .
Differential Analysis of Age, Gender, Race, Sentiment, and Emotion in Substance Use Discourse on Twitter During the COVID-19 Pandemic: A Natural Language Processing Approach

Differential Analysis of Age, Gender, Race, Sentiment, and Emotion in Substance Use Discourse on Twitter During the COVID-19 Pandemic: A Natural Language Processing Approach

Differential Analysis of Age, Gender, Race, Sentiment, and Emotion in Substance Use Discourse on Twitter During the COVID-19 Pandemic: A Natural Language Processing Approach

Authors of this article:

Julina Maharjan1 Author Orcid Image ;   Ruoming Jin1 Author Orcid Image ;   Jennifer King2 Author Orcid Image ;   Jianfeng Zhu1 Author Orcid Image ;   Deric Kenne2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Julina Maharjan   1 , BE ;   Ruoming Jin   1 , Prof Dr ;   Jennifer King   2 , Prof Dr ;   Jianfeng Zhu   1 , PhD ;   Deric Kenne   2 , Prof Dr

1 Department of Computer Science, Kent State University, Kent, OH, United States

2 Department of Public Health, Kent State University, Kent, OH, United States

Corresponding Author:

  • Julina Maharjan, BE
  • Department of Computer Science
  • Kent State University
  • 800 E. Summit St.
  • Kent, OH 44242
  • United States
  • Phone: 1 3305931365
  • Email: jmaharja@kent.edu