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

Grigori Sidorov1, Muhammad Ahmad1, Pierpaolo Basile2

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Summary
This summary is machine-generated.

Social media platforms like Reddit can be used for real-time toxicovigilance. An automated system using large language models (LLMs) accurately tracked opioid misuse discussions, correlating with mortality data.

Keywords:
CDCCenters for Disease Control and PreventionLLMRedditartificial intelligencedata miningdrug analysishealth carelarge language modelsopioid overdosesocial mediatemporal analysis

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Area of Science:

  • Public Health Surveillance
  • Computational Social Science
  • Toxicology

Background:

  • Opioid overdose is a critical global health issue, with traditional monitoring systems lacking real-time capabilities.
  • Social media platforms, particularly Reddit, offer a rich source of user-generated content for timely toxicovigilance.
  • Existing methods struggle to provide immediate insights into evolving opioid use patterns and associated risks.

Purpose of the Study:

  • To evaluate Reddit as a high-volume, real-time data source for toxicovigilance.
  • To develop an automated system for classifying and analyzing opioid-related social media posts.
  • To monitor public discourse on opioid use and detect behavioral patterns and trends.

Main Methods:

  • Collected a 6-year dataset (2018-2023) of Reddit posts using a comprehensive opioid lexicon.
  • Developed a natural language processing (NLP) pipeline, including machine learning and a fine-tuned large language model (LLM; OpenAI GPT-3.5 Turbo).
  • Analyzed temporal trends in classified posts and correlated them with Centers for Disease Control and Prevention (CDC) mortality data.

Main Results:

  • The fine-tuned GPT-3.5 Turbo LLM achieved a classification accuracy of 0.93, outperforming baseline models.
  • Temporal analysis revealed evolving trends in opioid-related discussions and user behavior over time.
  • A significant positive correlation (r=0.854, P<.001) was found between social media discussions of opioid misuse and CDC mortality data.

Conclusions:

  • Integrating NLP and LLMs with social media data enables effective real-time public health surveillance.
  • Reddit serves as a valuable platform for identifying emerging trends in opioid use and overdose risk.
  • The developed system provides a proactive tool for understanding and responding to the opioid crisis.