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

Infoveillance and Social Listening (313) Machine Learning (2052) Natural Language Processing (903) Substance Abuse (528) Opioid and Related Substance Misuse (199) Generative Language Models Including ChatGPT (689) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1907)

Published on in Vol 5 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70525, first published .
Sentiment Analysis Using a Large Language Model–Based Approach to Detect Opioids Mixed With Other Substances Via Social Media: Method Development and Validation

Sentiment Analysis Using a Large Language Model–Based Approach to Detect Opioids Mixed With Other Substances Via Social Media: Method Development and Validation

Sentiment Analysis Using a Large Language Model–Based Approach to Detect Opioids Mixed With Other Substances Via Social Media: Method Development and Validation

Authors of this article:

Muhammad Ahmad1 Author Orcid Image ;   Ildar Batyrshin1 Author Orcid Image ;   Grigori Sidorov1 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Usman M, Ahmad M, Sidorov G, Gelbukh I, Tellez R. A Large Language Model-Based Approach for Multilingual Hate Speech Detection on Social Media. Computers 2025;14(7):279 View
  2. Areia C, Taylor M, Garcia M, Hernandez J. Sentiment analysis of research attention: the Altmetric proof of concept. Frontiers in Research Metrics and Analytics 2025;10 View
  3. Sidorov G, Ahmad M, Basile P, Waqas M, Orji R, Batyrshin I. Monitoring Opioid-Related Social Media Chatter Using Natural Language Processing and Large Language Models: Temporal Analysis. JMIR Infodemiology 2025;5:e77279 View

Books/Policy Documents

  1. Ahmad M, Ullah F, Habiba U, Zamir M, Batyrshin I, Gelbukh A, Sidorov G. Advances in Soft Computing. View