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
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