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

Infoveillance and Social Listening (393) Infodemiology and Infoveillance (1966) Natural Language Processing (1227) Opioid and Related Substance Misuse (234) Generative Language Models Including ChatGPT (1419)

Published on in Vol 5 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77279, first published .
Woman overwhelmed by opioid addiction, drugs, and overdose, with social media logos.

Monitoring Opioid-Related Social Media Chatter Using Natural Language Processing and Large Language Models: Temporal Analysis

Monitoring Opioid-Related Social Media Chatter Using Natural Language Processing and Large Language Models: Temporal Analysis

Authors of this article:

Grigori Sidorov1 Author Orcid Image ;   Muhammad Ahmad1 Author Orcid Image ;   Pierpaolo Basile2 Author Orcid Image ;   Muhammad Waqas3 Author Orcid Image ;   Rita Orji4 Author Orcid Image ;   Ildar Batyrshin1 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Atinga R, Nyarko S, Akoriyea S. Leveraging Artificial Intelligence for Substance Use Prevention Among Adolescents: A Systematic Review of Emerging Evidence. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 2026;63 View
  2. Zhang R, Kimura K, Yoshida N. Methods for Detecting Suspicious Information From Individual Transactions of Pharmaceutical Products via Twitter (now X): Retrospective Observational Study. Journal of Medical Internet Research 2026;28:e91103 View
  3. Ahmad M, Orji R, Ullah F, Batyrshin I, Sidorov G. Detecting Opioid Misuse on Social Media via Named Entity Recognition (NER) With Deep Learning. Expert Systems 2026;43(8) View
  4. Counts C, Spadaro A, Lakamana S, Sarker A, Wightman R, Love J, Calello D, Perrone J. Self-Reported Tianeptine Experiences on Reddit: Natural Language Processing–Assisted Qualitative Study. JMIR Infodemiology 2026;6:e86683 View