# Mental Health Coping Stories on Social Media: A Causal-Inference Study of Papageno Effect

arXiv: https://arxiv.org/abs/2302.09885 · HTML: https://mlsanity.com/paper/2302.09885/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 64 references that are in the map.
- First posted on arXiv 20 Feb 2023.

## Builds on (most cited first, 2 of 2)

- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [Detecting potentially harmful and protective suicide-related content on twitter: A machine learning approach](https://mlsanity.com/paper/2112.04796/) (2021)

## Built on by (most cited first, 12 of 12)

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- [RubRIX: Rubric-Driven Risk Mitigation in Caregiver-AI Interactions](https://mlsanity.com/paper/2601.13235/) (2026)
- [Mental Health Impacts of AI Companions: Triangulating Social Media Quasi-Experiments, User Perspectives, and Relational Theory](https://mlsanity.com/paper/2509.22505/) (2025)
- [Explainable AI for Mental Disorder Detection via Social Media: A survey and outlook](https://mlsanity.com/paper/2406.05984/) (2024)
- [Linguistic Comparison of AI- and Human-Written Responses to Online Mental Health Queries](https://mlsanity.com/paper/2504.09271/) (2025)
- [AI Psychosis: Does Conversational AI Amplify Delusion-Related Language?](https://mlsanity.com/paper/2603.19574/) (2026)
- [The Hidden Toll of Social Media News: Causal Effects on Psychosocial Wellbeing](https://mlsanity.com/paper/2601.13487/) (2026)
- [Detecting Early and Implicit Suicidal Ideation via Longitudinal and Information Environment Signals on Social Media](https://mlsanity.com/paper/2510.14889/) (2025)
- [LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback](https://mlsanity.com/paper/2605.30273/) (2026)
- [Catalysts of Conversation: Examining Interaction Dynamics Between Topic Initiators and Commentors in Alzheimer's Disease Online Communities](https://mlsanity.com/paper/2412.13388/) (2024)
- [Algorithmic Cultivation: How Social Media Feeds Shape User Language](https://mlsanity.com/paper/2605.17010/) (2026)
- [Disrupted Companionship: A Risk Assessment Framework and Cross-Platform Quantitative Analysis of Psychosocial Responses to AI Companion Disruptions](https://mlsanity.com/paper/2609.16907/) (2026)

## Abstract (arXiv)

The Papageno effect concerns how media can play a positive role in preventing and mitigating suicidal ideation and behaviors. With the increasing ubiquity and widespread use of social media, individuals often express and share lived experiences and struggles with mental health. However, there is a gap in our understanding about the existence and effectiveness of the Papageno effect in social media, which we study in this paper. In particular, we adopt a causal-inference framework to examine the impact of exposure to mental health coping stories on individuals on Twitter. We obtain a Twitter dataset with ~2M posts by ~10K individuals. We consider engaging with coping stories as the Treatment intervention, and adopt a stratified propensity score approach to find matched cohorts of Treatment and Control individuals. We measure the psychosocial shifts in affective, behavioral, and cognitive outcomes in longitudinal Twitter data before and after engaging with the coping stories. Our findings reveal that, engaging with coping stories leads to decreased stress and depression, and improved expressive writing, diversity, and interactivity. Our work discusses the practical and platform design implications in supporting mental wellbeing.