# Words Matter: Reducing Stigma in Online Conversations about Substance Use with Large Language Models

arXiv: https://arxiv.org/abs/2408.07873 · HTML: https://mlsanity.com/paper/2408.07873/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 50 references that are in the map.
- First posted on arXiv 15 Aug 2024.

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

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Constitutional AI: Harmlessness from AI Feedback](https://mlsanity.com/paper/2212.08073/) (2022)
- [BERTopic: Neural topic modeling with a class-based TF-IDF procedure](https://mlsanity.com/paper/2203.05794/) (2022)
- [GoEmotions: A Dataset of Fine-Grained Emotions](https://mlsanity.com/paper/2005.00547/) (2020)
- [A Survey of Evaluation Metrics Used for NLG Systems](https://mlsanity.com/paper/2008.12009/) (2020)
- [Automatically Neutralizing Subjective Bias in Text](https://mlsanity.com/paper/1911.09709/) (2019)
- [Text Detoxification using Large Pre-trained Neural Models](https://mlsanity.com/paper/2109.08914/) (2021)
- [Bias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification Tasks](https://mlsanity.com/paper/2306.05550/) (2023)
- [Modeling Framing in Immigration Discourse on Social Media](https://mlsanity.com/paper/2104.06443/) (2021)
- [A Framework for the Computational Linguistic Analysis of Dehumanization](https://mlsanity.com/paper/2003.03014/) (2020)
- [An Investigation of Large Language Models for Real-World Hate Speech Detection](https://mlsanity.com/paper/2401.03346/) (2024)
- [Decoding the Narratives: Analyzing Personal Drug Experiences Shared on Reddit](https://mlsanity.com/paper/2406.12117/) (2024)
- [Pitfalls of Conversational LLMs on News Debiasing](https://mlsanity.com/paper/2404.06488/) (2024)

## Built on by (most cited first, 3 of 3)

- [Navigating the Rabbit Hole: Emergent Biases in LLM-Generated Attack Narratives Targeting Mental Health Groups](https://mlsanity.com/paper/2504.06160/) (2025)
- [Exposure to Content Written by Large Language Models Can Reduce Stigma Around Opioid Use Disorder in Online Communities](https://mlsanity.com/paper/2504.10501/) (2025)
- [Stigma and Support in Online Sexual Violence Narratives on Reddit](https://mlsanity.com/paper/2608.11433/) (2026)

## Abstract (arXiv)

Stigma is a barrier to treatment for individuals struggling with substance use disorders (SUD), which leads to significantly lower treatment engagement rates. With only 7% of those affected receiving any form of help, societal stigma not only discourages individuals with SUD from seeking help but isolates them, hindering their recovery journey and perpetuating a cycle of shame and self-doubt. This study investigates how stigma manifests on social media, particularly Reddit, where anonymity can exacerbate discriminatory behaviors. We analyzed over 1.2 million posts, identifying 3,207 that exhibited stigmatizing language towards people who use substances (PWUS). Using Informed and Stylized LLMs, we develop a model for de-stigmatization of these expressions into empathetic language, resulting in 1,649 reformed phrase pairs. Our paper contributes to the field by proposing a computational framework for analyzing stigma and destigmatizing online content, and delving into the linguistic features that propagate stigma towards PWUS. Our work not only enhances understanding of stigma's manifestations online but also provides practical tools for fostering a more supportive digital environment for those affected by SUD. Code and data will be made publicly available upon acceptance.