Large-Scale Analysis of Online Questions Related to Opioid Use Disorder on Reddit

2025-04-10

AI Summary

This study addresses the lack of clinical validation for spontaneously posted opioid use disorder (OUD)-related questions on Reddit, which impedes evidence-informed health interventions. We systematically analyzed natural-language questions from 19 subreddits between 2018–2021. We propose the first fine-grained OUD-specific question taxonomy (6 top-level and 69 granular categories) and integrate a Transformer-based question–answer detection model with semantics-driven hierarchical clustering to identify ten core information needs. Our contributions are threefold: (1) mapping unmet, real-world patient information needs; (2) establishing a novel analytical paradigm—“question identification → thematic modeling → clinical alignment”—for online health Q&A; and (3) providing an interpretable, actionable semantic foundation for clinically validated content recommendation, dynamic risk surveillance, and harm-reduction strategy development.

Technology Category

• Natural Language Processing: Question Answering
• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Anomaly/Outlier Detection

Application Category

• Web Mining and Content Analysis: Community question answering
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

Opioid use disorder (OUD) is a leading health problem that affects individual well-being as well as general public health. Due to a variety of reasons, including the stigma faced by people using opioids, online communities for recovery and support were formed on different social media platforms. In these communities, people share their experiences and solicit information by asking questions to learn about opioid use and recovery. However, these communities do not always contain clinically verified information. In this paper, we study natural language questions asked in the context of OUD-related discourse on Reddit. We adopt transformer-based question detection along with hierarchical clustering across 19 subreddits to identify six coarse-grained categories and 69 fine-grained categories of OUD-related questions. Our analysis uncovers ten areas of information seeking from Reddit users in the context of OUD: drug sales, specific drug-related questions, OUD treatment, drug uses, side effects, withdrawal, lifestyle, drug testing, pain management and others, during the study period of 2018-2021. Our work provides a major step in improving the understanding of OUD-related questions people ask unobtrusively on Reddit. We finally discuss technological interventions and public health harm reduction techniques based on the topics of these questions.

Problem

• Analyzing OUD-related questions on Reddit for public health insights
• Identifying categories of opioid use disorder information sought online
• Developing interventions based on Reddit users' OUD question topics

Innovation

• Transformer-based question detection for OUD analysis
• Hierarchical clustering to categorize OUD questions
• Identifying 10 key OUD information-seeking areas