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

Public (e)Health, Digital Epidemiology and Public Health Informatics (1008) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1911) Infodemiology and Infoveillance (1558) Natural Language Processing (917) Theme Issue: Medical Informatics and COVID-19 (124) Pharmacovigilance (171)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63755, first published .
Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis

Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis

Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis

Authors of this article:

Wanxin Li1 Author Orcid Image ;   Yining Hua2, 3 Author Orcid Image ;   Peilin Zhou4 Author Orcid Image ;   Li Zhou3 Author Orcid Image ;   Xin Xu1 Author Orcid Image ;   Jie Yang1, 5 Author Orcid Image
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