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

arXiv: https://arxiv.org/abs/2504.08044 · HTML: https://mlsanity.com/paper/2504.08044/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 111 references that are in the map.
- First posted on arXiv 10 Apr 2025.

## Builds on (most cited first, 13 of 13)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction](https://mlsanity.com/paper/1802.03426/) (2018)
- [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://mlsanity.com/paper/1908.08962/) (2019)
- [Pre-trained Summarization Distillation](https://mlsanity.com/paper/2010.13002/) (2020)
- [An Empirical Study of Obsolete Answers on Stack Overflow](https://mlsanity.com/paper/1903.12282/) (2019)
- [What Makes Online Communities 'Better'? Measuring Values, Consensus, and Conflict across Thousands of Subreddits](https://mlsanity.com/paper/2111.05835/) (2021)
- [The Effect of Moderation on Online Mental Health Conversations](https://mlsanity.com/paper/2005.09225/) (2020)
- [Leveraging Prompt-Based Large Language Models: Predicting Pandemic Health Decisions and Outcomes Through Social Media Language](https://mlsanity.com/paper/2403.00994/) (2024)
- [Characterizing Information Seeking Events in Health-Related Social Discourse](https://mlsanity.com/paper/2308.09156/) (2023)
- [Essential Sentences for Navigating Stack Overflow Answers](https://mlsanity.com/paper/1912.13455/) (2019)
- [Theme-driven Keyphrase Extraction to Analyze Social Media Discourse](https://mlsanity.com/paper/2301.11508/) (2023)
- [A Large-Scale Study of the Twitter Follower Network to Characterize the Spread of Prescription Drug Abuse Tweets](https://mlsanity.com/paper/2102.08661/) (2021)
- [Patterns of Routes of Administration and Drug Tampering for Nonmedical Opioid Consumption: Data Mining and Content Analysis of Reddit Discussions](https://mlsanity.com/paper/2102.11235/) (2021)

## Built on by (most cited first, 1 of 1)

- [SABIA: An AI-Powered Tool for Detecting Opioid-Related Behaviors on Social Media](https://mlsanity.com/paper/2508.10046/) (2025)

## Abstract (arXiv)

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.