# A Survey on Multilingual Mental Disorders Detection from Social Media Data

arXiv: https://arxiv.org/abs/2505.15556 · HTML: https://mlsanity.com/paper/2505.15556/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 28 of its 195 references that are in the map.
- First posted on arXiv 21 May 2025.

## Builds on (most cited first, 28 of 28)

- [The State and Fate of Linguistic Diversity and Inclusion in the NLP World](https://mlsanity.com/paper/2004.09095/) (2020)
- [SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)](https://mlsanity.com/paper/2006.07235/) (2020)
- [Some Languages are More Equal than Others: Probing Deeper into the Linguistic Disparity in the NLP World](https://mlsanity.com/paper/2210.08523/) (2022)
- [On the State of Social Media Data for Mental Health Research](https://mlsanity.com/paper/2011.05233/) (2020)
- [Latent Suicide Risk Detection on Microblog via Suicide-Oriented Word Embeddings and Layered Attention](https://mlsanity.com/paper/1910.12038/) (2019)
- [Data set creation and empirical analysis for detecting signs of depression from social media postings](https://mlsanity.com/paper/2202.03047/) (2022)
- [Identifying Depressive Symptoms from Tweets: Figurative Language Enabled Multitask Learning Framework](https://mlsanity.com/paper/2011.06149/) (2020)
- [It's Just a Matter of Time: Detecting Depression with Time-Enriched Multimodal Transformers](https://mlsanity.com/paper/2301.05453/) (2023)
- [Gender and Racial Fairness in Depression Research using Social Media](https://mlsanity.com/paper/2103.10550/) (2021)
- [Identifying Moments of Change from Longitudinal User Text](https://mlsanity.com/paper/2205.05593/) (2022)
- [Early Risk Detection of Pathological Gambling, Self-Harm and Depression Using BERT](https://mlsanity.com/paper/2106.16175/) (2021)
- [DEPTWEET: A Typology for Social Media Texts to Detect Depression Severities](https://mlsanity.com/paper/2210.05372/) (2022)
- [Diverse Perspectives, Divergent Models: Cross-Cultural Evaluation of Depression Detection on Twitter](https://mlsanity.com/paper/2406.15362/) (2024)
- [Not Just Depressed: Bipolar Disorder Prediction on Reddit](https://mlsanity.com/paper/1811.04655/) (2018)
- [SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection](https://mlsanity.com/paper/2503.07269/) (2025)
- [Cross-Cultural Differences in Mental Health Expressions on Social Media](https://mlsanity.com/paper/2402.11477/) (2024)
- [Temporal Mental Health Dynamics on Social Media](https://mlsanity.com/paper/2008.13121/) (2020)
- [Detecting Depression in Thai Blog Posts: a Dataset and a Baseline](https://mlsanity.com/paper/2111.04574/) (2021)
- [Harnessing Large Language Models Over Transformer Models for Detecting Bengali Depressive Social Media Text: A Comprehensive Study](https://mlsanity.com/paper/2401.07310/) (2024)
- [On the State of NLP Approaches to Modeling Depression in Social Media: A Post-COVID-19 Outlook](https://mlsanity.com/paper/2410.08793/) (2024)
- [Datasets for Depression Modeling in Social Media: An Overview](https://mlsanity.com/paper/2503.21513/) (2025)
- [Using Linguistic Features to Estimate Suicide Probability of Chinese Microblog Users](https://mlsanity.com/paper/1411.0861/) (2014)
- [See and Read: Detecting Depression Symptoms in Higher Education Students Using Multimodal Social Media Data](https://mlsanity.com/paper/1912.01131/) (2019)
- [A Comprehensive Evaluation of Large Language Models on Mental Illnesses in Arabic Context](https://mlsanity.com/paper/2501.06859/) (2025)
- [Hybrid approach to detecting symptoms of depression in social media entries](https://mlsanity.com/paper/2106.10485/) (2021)
- [Leveraging LLMs for Translating and Classifying Mental Health Data](https://mlsanity.com/paper/2410.12985/) (2024)
- [Topical differences between Chinese language Twitter and Sina Weibo](https://mlsanity.com/paper/1512.07281/) (2015)
- [Lexicography Saves Lives (LSL): Automatically Translating Suicide-Related Language](https://mlsanity.com/paper/2412.15497/) (2024)

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

- [Uncertainty-aware Semi-supervised Ensemble Teacher Framework for Multilingual Depression Detection](https://mlsanity.com/paper/2512.24772/) (2025)
- [Towards Efficient and Robust Linguistic Emotion Diagnosis for Mental Health via Multi-Agent Instruction Refinement](https://mlsanity.com/paper/2601.13481/) (2026)
- [PsihoRo: Depression and Anxiety Romanian Text Corpus](https://mlsanity.com/paper/2602.18324/) (2026)

## Abstract (arXiv)

The increasing prevalence of mental disorders globally highlights the urgent need for effective digital screening methods that can be used in multilingual contexts. Most existing studies, however, focus on English data, overlooking critical mental health signals that may be present in non-English texts. To address this gap, we present a survey of the detection of mental disorders using social media data beyond the English language. We compile a comprehensive list of 108 datasets spanning 25 languages that can be used for developing NLP models for mental health screening. In addition, we discuss the cultural nuances that influence online language patterns and self-disclosure behaviors, and how these factors can impact the performance of NLP tools. Our survey highlights major challenges, including the scarcity of resources for low- and mid-resource languages and the dominance of depression-focused data over other disorders. By identifying these gaps, we advocate for interdisciplinary collaborations and the development of multilingual benchmarks to enhance mental health screening worldwide.