Monitoring Opioid-Related Social Media Chatter Using Natural Language Processing and Large Language Models: Temporal Analysis
This study demonstrates the potential of integrating advanced natural language processing techniques and LLMs with social media data to support real-time public health surveillance. Reddit provides a valuable platform for identifying emerging trends in opioid use and overdose risk. The proposed system offers a proactive tool for researchers, clinicians, and policymakers to better understand and respond to the opioid crisis.
Authors
- Grigori Sidorov (ORCID: https://orcid.org/0000-0003-3901-3522)
- Ildar Batyrshin (ORCID: https://orcid.org/0000-0003-0241-7902)
- Rita Orji (ORCID: https://orcid.org/0000-0001-6152-8034)
- Pierpaolo Basile (ORCID: https://orcid.org/0000-0002-0545-1105)
- Muhammad Waqas (ORCID: https://orcid.org/0000-0003-2534-6916)
- Muhammad Ahmad (ORCID: https://orcid.org/0009-0003-8799-8212)
Institutions
- Dalhousie University (CA)
- Islamia University of Bahawalpur (PK)
- University of Bari Aldo Moro (IT)
- Instituto Politécnico Nacional (MX)
Publication Details
- Journal
- JMIR Infodemiology
- Published
- 2025-11-04
- DOI
- https://doi.org/10.2196/77279
- Citations
- 1
- Primary Topic
- Mental Health via Writing
- Type
- article
- Field-Weighted Citation Impact
- 2.44