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

Early Results in Infodemiology and Infoveillance (94) Natural Language Processing (831) Infodemiology and Infoveillance (1484) Opioid and Related Substance Misuse (184) Artificial Intelligence (1840)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57395, first published .
Public Health Discussions on Social Media: Evaluating Automated Sentiment Analysis Methods

Public Health Discussions on Social Media: Evaluating Automated Sentiment Analysis Methods

Public Health Discussions on Social Media: Evaluating Automated Sentiment Analysis Methods

Authors of this article:

Lisa M Gandy1 Author Orcid Image ;   Lana V Ivanitskaya2 Author Orcid Image ;   Leeza L Bacon3 Author Orcid Image ;   Rodina Bizri-Baryak2 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Bizri-Baryak R, Ivanitskaya L, Erzikova E, Kreps G. Analyzing the Overturn of Roe v. Wade: A Term Co-Occurrence Network Analysis of YouTube Comments. Informatics 2025;12(2):49 View
  2. Ahmad M, Batyrshin I, Sidorov G. Sentiment Analysis Using a Large Language Model–Based Approach to Detect Opioids Mixed With Other Substances Via Social Media: Method Development and Validation. JMIR Infodemiology 2025;5:e70525 View

Conference Proceedings

  1. Vaz N, Silva K, Velasco G, Mata L, Fernandes D, Carvalho S. Anais do XXV Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS 2025). Towards a Personalized mHealth Model Using Intelligent Conversational Agents View