mlsanityData to 7 Oct 2026

Suicidal Ideation and Mental Disorder Detection with Attentive Relation Networks

arXiv 2004.07601 ↗First posted 16 Apr 2020cs.CL cs.CY cs.LGcited by 28

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Abstract (arXiv)

Mental health is a critical issue in modern society, and mental disorders could sometimes turn to suicidal ideation without effective treatment. Early detection of mental disorders and suicidal ideation from social content provides a potential way for effective social intervention. However, classifying suicidal ideation and other mental disorders is challenging as they share similar patterns in language usage and sentimental polarity. This paper enhances text representation with lexicon-based sentiment scores and latent topics and proposes using relation networks to detect suicidal ideation and mental disorders with related risk indicators. The relation module is further equipped with the attention mechanism to prioritize more critical relational features. Through experiments on three real-world datasets, our model outperforms most of its counterparts.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Apr 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 1; 2023: 6; 2024: 8; 2025: 7; 2026: 5.

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  1. 2021MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcarecited by 159
  2. 2023MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Modelscited by 63
  3. 2023Towards Interpretable Mental Health Analysis with Large Language Modelscited by 53
  4. 2024Large Language Models in Mental Health Care: a Scoping Reviewcited by 34
  5. 2022A Unified Review of Deep Learning for Automated Medical Codingcited by 26
  6. 2023Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Healthcited by 25
  7. 2023ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?cited by 15
  8. 2024Large Language Model for Mental Health: A Systematic Reviewcited by 14
  9. 2025A Systematic Evaluation of LLM Strategies for Mental Health Text Analysis: Fine-tuning vs. Prompt Engineering vs. RAGcited by 14
  10. 2023Emotion fusion for mental illness detection from social media: A surveycited by 13
  11. 2024Private Synthetic Text Generation with Diffusion Modelscited by 10
  12. 2023ChatGPT for Suicide Risk Assessment on Social Media: Quantitative Evaluation of Model Performance, Potentials and Limitationscited by 9
16 more
  1. 2024MentalGLM Series: Explainable Large Language Models for Mental Health Analysis on Chinese Social Mediacited by 9
  2. 2024A Comprehensive Evaluation of Large Language Models on Mental Illnessescited by 7
  3. 2025Survey and Experiments on Mental Disorder Detection via Social Media: From Large Language Models and RAG to Agentscited by 6
  4. 2024Unveiling and Mitigating Bias in Mental Health Analysis with Large Language Modelscited by 5
  5. 2025Human Behavior Atlas: Benchmarking Unified Psychological and Social Behavior Understandingcited by 5
  6. 2024CASE: Efficient Curricular Data Pre-training for Building Assistive Psychology Expert Modelscited by 1
  7. 2024Lexicography Saves Lives (LSL): Automatically Translating Suicide-Related Languagecited by 1
  8. 2025Differentially-private text generation degrades output language qualitycited by 1
  9. 2025Mental Multi-class Classification on Social Media: Benchmarking Transformer Architectures against LSTM Modelscited by 1
  10. 2026TrustMH-Bench: A Comprehensive Benchmark for Evaluating the Trustworthiness of Large Language Models in Mental Healthcited by 1
  11. 2025Rethinking Suicidal Ideation Detection: A Trustworthy Annotation Framework and Cross-Lingual Model Evaluationcited by 0
  12. 2025multiMentalRoBERTa: A Fine-tuned Multiclass Classifier for Mental Health Disordercited by 0
  13. 2026Enhancing Mental Health Classification with Layer-Attentive Residuals and Contrastive Feature Learningcited by 0
  14. 2026Improving Mental Health Screening and Early Risk Detection in Spanishcited by 0
  15. 2026Reading Anxiety or Reading the Label? Comparing Fine-Tuned and Frontier Models for Anxiety Detection on Social Mediacited by 0
  16. 2026From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Healthcited by 0