# Latent Suicide Risk Detection on Microblog via Suicide-Oriented Word Embeddings and Layered Attention

arXiv: https://arxiv.org/abs/1910.12038 · HTML: https://mlsanity.com/paper/1910.12038/

## Key facts

- Cited by 27 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Oct 2019.

## Built on by (most cited first, 27 of 27)

- [PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support](https://mlsanity.com/paper/2106.01702/) (2021)
- [CAMS: An Annotated Corpus for Causal Analysis of Mental Health Issues in Social Media Posts](https://mlsanity.com/paper/2207.04674/) (2022)
- [Identifying Moments of Change from Longitudinal User Text](https://mlsanity.com/paper/2205.05593/) (2022)
- [Characterizing the Entities in Harmful Memes: Who is the Hero, the Villain, the Victim?](https://mlsanity.com/paper/2301.11219/) (2023)
- [Learning Models for Suicide Prediction from Social Media Posts](https://mlsanity.com/paper/2105.03315/) (2021)
- [PsyGUARD: An Automated System for Suicide Detection and Risk Assessment in Psychological Counseling](https://mlsanity.com/paper/2409.20243/) (2024)
- [Supervised Learning and Large Language Model Benchmarks on Mental Health Datasets: Cognitive Distortions and Suicidal Risks in Chinese Social Media](https://mlsanity.com/paper/2309.03564/) (2023)
- [MentalGLM Series: Explainable Large Language Models for Mental Health Analysis on Chinese Social Media](https://mlsanity.com/paper/2410.10323/) (2024)
- [Sequence-to-Sequence Lexical Normalization with Multilingual Transformers](https://mlsanity.com/paper/2110.02869/) (2021)
- [Benchmarking for Public Health Surveillance tasks on Social Media with a Domain-Specific Pretrained Language Model](https://mlsanity.com/paper/2204.04521/) (2022)
- [Exploring Social Media for Early Detection of Depression in COVID-19 Patients](https://mlsanity.com/paper/2302.12044/) (2023)
- [Explainable AI for Mental Disorder Detection via Social Media: A survey and outlook](https://mlsanity.com/paper/2406.05984/) (2024)
- [Towards Suicide Prevention from Bipolar Disorder with Temporal Symptom-Aware Multitask Learning](https://mlsanity.com/paper/2307.00995/) (2023)
- [Creation and evaluation of timelines for longitudinal user posts](https://mlsanity.com/paper/2303.05891/) (2023)
- [WellXplain: Wellness Concept Extraction and Classification in Reddit Posts for Mental Health Analysis](https://mlsanity.com/paper/2308.13710/) (2023)
- [A Survey on Multilingual Mental Disorders Detection from Social Media Data](https://mlsanity.com/paper/2505.15556/) (2025)
- [Quantifying the Suicidal Tendency on Social Media: A Survey](https://mlsanity.com/paper/2110.03663/) (2021)
- [NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Media](https://mlsanity.com/paper/2301.11004/) (2023)
- [Sig-Networks Toolkit: Signature Networks for Longitudinal Language Modelling](https://mlsanity.com/paper/2312.03523/) (2023)
- [Mental-R1: Aligning LLM Reasoning for Mental Health Assessment](https://mlsanity.com/paper/2606.13176/) (2026)
- [3M-Health: Multimodal Multi-Teacher Knowledge Distillation for Mental Health Detection](https://mlsanity.com/paper/2407.09020/) (2024)
- [Lexicography Saves Lives (LSL): Automatically Translating Suicide-Related Language](https://mlsanity.com/paper/2412.15497/) (2024)
- [Mental Health Assessment for the Chatbots](https://mlsanity.com/paper/2201.05382/) (2022)
- [Robin: A Novel Online Suicidal Text Corpus of Substantial Breadth and Scale](https://mlsanity.com/paper/2209.05707/) (2022)
- [Risk prediction of pathological gambling on social media](https://mlsanity.com/paper/2403.19358/) (2024)
- [Leveraging Large Language Models for Spontaneous Speech-Based Suicide Risk Detection](https://mlsanity.com/paper/2507.00693/) (2025)
- [Reading Between the Signs: Predicting Future Suicidal Ideation from Adolescent Social Media Texts](https://mlsanity.com/paper/2509.03530/) (2025)

## Abstract (arXiv)

Despite detection of suicidal ideation on social media has made great progress in recent years, people's implicitly and anti-real contrarily expressed posts still remain as an obstacle, constraining the detectors to acquire higher satisfactory performance. Enlightened by the hidden "tree holes" phenomenon on microblog, where people at suicide risk tend to disclose their inner real feelings and thoughts to the microblog space whose authors have committed suicide, we explore the use of tree holes to enhance microblog-based suicide risk detection from the following two perspectives. (1) We build suicide-oriented word embeddings based on tree hole contents to strength the sensibility of suicide-related lexicons and context based on tree hole contents. (2) A two-layered attention mechanism is deployed to grasp intermittently changing points from individual's open blog streams, revealing one's inner emotional world more or less. Our experimental results show that with suicide-oriented word embeddings and attention, microblog-based suicide risk detection can achieve over 91% accuracy. A large-scale well-labelled suicide data set is also reported in the paper.