# CAMS: An Annotated Corpus for Causal Analysis of Mental Health Issues in Social Media Posts

arXiv: https://arxiv.org/abs/2207.04674 · HTML: https://mlsanity.com/paper/2207.04674/

## Key facts

- Cited by 34 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 47 references that are in the map.
- First posted on arXiv 11 Jul 2022.

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

- [GoEmotions: A Dataset of Fine-Grained Emotions](https://mlsanity.com/paper/2005.00547/) (2020)
- [Dual Attention Networks for Multimodal Reasoning and Matching](https://mlsanity.com/paper/1611.00471/) (2016)
- [Depression and Self-Harm Risk Assessment in Online Forums](https://mlsanity.com/paper/1709.01848/) (2017)
- [Dreaddit: A Reddit Dataset for Stress Analysis in Social Media](https://mlsanity.com/paper/1911.00133/) (2019)
- [SMHD: A Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions](https://mlsanity.com/paper/1806.05258/) (2018)
- [Deep Learning for Suicide and Depression Identification with Unsupervised Label Correction](https://mlsanity.com/paper/2102.09427/) (2021)
- [Latent Suicide Risk Detection on Microblog via Suicide-Oriented Word Embeddings and Layered Attention](https://mlsanity.com/paper/1910.12038/) (2019)
- [Causal Understanding of Fake News Dissemination on Social Media](https://mlsanity.com/paper/2010.10580/) (2020)
- [Causal Explanation Analysis on Social Media](https://mlsanity.com/paper/1809.01202/) (2018)
- [Building and Using Personal Knowledge Graph to Improve Suicidal Ideation Detection on Social Media](https://mlsanity.com/paper/2012.09123/) (2020)
- [Data Augmentation for Mental Health Classification on Social Media](https://mlsanity.com/paper/2112.10064/) (2021)
- [From Stance to Concern: Adaptation of Propositional Analysis to New Tasks and Domains](https://mlsanity.com/paper/2203.10659/) (2022)
- [Quantifying the Suicidal Tendency on Social Media: A Survey](https://mlsanity.com/paper/2110.03663/) (2021)

## Built on by (most cited first, 30 of 34)

- [MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models](https://mlsanity.com/paper/2309.13567/) (2023)
- [Towards Interpretable Mental Health Analysis with Large Language Models](https://mlsanity.com/paper/2304.03347/) (2023)
- [Large Language Models in Mental Health Care: a Scoping Review](https://mlsanity.com/paper/2401.02984/) (2024)
- [Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Health](https://mlsanity.com/paper/2304.10447/) (2023)
- [From Personas to Talks: Revisiting the Impact of Personas on LLM-Synthesized Emotional Support Conversations](https://mlsanity.com/paper/2502.11451/) (2025)
- [The Rise of Small Language Models in Healthcare: A Comprehensive Survey](https://mlsanity.com/paper/2504.17119/) (2025)
- [ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?](https://mlsanity.com/paper/2311.16989/) (2023)
- [Large Language Model for Mental Health: A Systematic Review](https://mlsanity.com/paper/2403.15401/) (2024)
- [Still Not Quite There! Evaluating Large Language Models for Comorbid Mental Health Diagnosis](https://mlsanity.com/paper/2410.03908/) (2024)
- [MentalGLM Series: Explainable Large Language Models for Mental Health Analysis on Chinese Social Media](https://mlsanity.com/paper/2410.10323/) (2024)
- [A Cross Attention Approach to Diagnostic Explainability using Clinical Practice Guidelines for Depression](https://mlsanity.com/paper/2311.13852/) (2023)
- [MHQA: A Diverse, Knowledge Intensive Mental Health Question Answering Challenge for Language Models](https://mlsanity.com/paper/2502.15418/) (2025)
- [Explainable Causal Analysis of Mental Health on Social Media Data](https://mlsanity.com/paper/2210.08430/) (2022)
- [LOST: A Mental Health Dataset of Low Self-esteem in Reddit Posts](https://mlsanity.com/paper/2306.05596/) (2023)
- [Clinical Insights: A Comprehensive Review of Language Models in Medicine](https://mlsanity.com/paper/2408.11735/) (2024)
- [What is Stigma Attributed to? A Theory-Grounded, Expert-Annotated Interview Corpus for Demystifying Mental-Health Stigma](https://mlsanity.com/paper/2505.12727/) (2025)
- [Interpretable Depression Detection from Social Media Text Using LLM-Derived Embeddings](https://mlsanity.com/paper/2506.06616/) (2025)
- [WellXplain: Wellness Concept Extraction and Classification in Reddit Posts for Mental Health Analysis](https://mlsanity.com/paper/2308.13710/) (2023)
- [MentalQA: An Annotated Arabic Corpus for Questions and Answers of Mental Healthcare](https://mlsanity.com/paper/2405.12619/) (2024)
- [NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Media](https://mlsanity.com/paper/2301.11004/) (2023)
- [LonXplain: Lonesomeness as a Consequence of Mental Disturbance in Reddit Posts](https://mlsanity.com/paper/2305.18736/) (2023)
- [Deep Knowledge-Infusion For Explainable Depression Detection](https://mlsanity.com/paper/2409.02122/) (2024)
- [AraHealthQA 2025: The First Shared Task on Arabic Health Question Answering](https://mlsanity.com/paper/2508.20047/) (2025)
- [TrustMH-Bench: A Comprehensive Benchmark for Evaluating the Trustworthiness of Large Language Models in Mental Health](https://mlsanity.com/paper/2603.03047/) (2026)
- [Predicting mental health using social media: A roadmap for future development](https://mlsanity.com/paper/2301.10453/) (2023)
- [Evaluating the Effectiveness of the Foundational Models for Q&A Classification in Mental Health care](https://mlsanity.com/paper/2406.15966/) (2024)
- [MentalArena: Self-play Training of Language Models for Diagnosis and Treatment of Mental Health Disorders](https://mlsanity.com/paper/2410.06845/) (2024)
- [P-ReMIS: Pragmatic Reasoning in Mental Health and a Social Implication](https://mlsanity.com/paper/2507.23247/) (2025)
- [OMIND: Framework for Knowledge Grounded Finetuning and Multi-Turn Dialogue Benchmark for Mental Health LLMs](https://mlsanity.com/paper/2603.25105/) (2026)
- [Causal Categorization of Mental Health Posts using Transformers](https://mlsanity.com/paper/2301.02589/) (2023)

## Abstract (arXiv)

Research community has witnessed substantial growth in the detection of mental health issues and their associated reasons from analysis of social media. We introduce a new dataset for Causal Analysis of Mental health issues in Social media posts (CAMS). Our contributions for causal analysis are two-fold: causal interpretation and causal categorization. We introduce an annotation schema for this task of causal analysis. We demonstrate the efficacy of our schema on two different datasets: (i) crawling and annotating 3155 Reddit posts and (ii) re-annotating the publicly available SDCNL dataset of 1896 instances for interpretable causal analysis. We further combine these into the CAMS dataset and make this resource publicly available along with associated source code: https://github.com/drmuskangarg/CAMS. We present experimental results of models learned from CAMS dataset and demonstrate that a classic Logistic Regression model outperforms the next best (CNN-LSTM) model by 4.9% accuracy.