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

ABSTRACT:

Background

Opioid overdose is a global public health emergency, with the United States experiencing high rates of morbidity and mortality due to prescription and illicit opioid use. Traditional public health monitoring systems often fail to provide real-time insights, limiting their capacity for early detection and intervention. Social media platforms, especially Reddit, offer a promising alternative for timely toxicovigilance due to the abundance of user-generated, real-time content.

Objective

This study aimed to explore the use of Reddit as a real-time, high-volume source for toxicovigilance and develop an automated system that can classify and analyze opioid-related social media posts to detect behavioral patterns and monitor the evolution of public discourse on opioid us

SUBMITTER: Sidorov G 

PROVIDER: S-EPMC12585000 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature