# Towards Suicide Prevention from Bipolar Disorder with Temporal Symptom-Aware Multitask Learning

arXiv: https://arxiv.org/abs/2307.00995 · HTML: https://mlsanity.com/paper/2307.00995/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 81 references that are in the map.
- First posted on arXiv 3 Jul 2023.

## Builds on (most cited first, 9 of 9)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Longformer: The Long-Document Transformer](https://mlsanity.com/paper/2004.05150/) (2020)
- [Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics](https://mlsanity.com/paper/1705.07115/) (2017)
- [SMHD: A Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions](https://mlsanity.com/paper/1806.05258/) (2018)
- [Latent Suicide Risk Detection on Microblog via Suicide-Oriented Word Embeddings and Layered Attention](https://mlsanity.com/paper/1910.12038/) (2019)
- [ConceptNet at SemEval-2017 Task 2: Extending Word Embeddings with Multilingual Relational Knowledge](https://mlsanity.com/paper/1704.03560/) (2017)
- [Not Just Depressed: Bipolar Disorder Prediction on Reddit](https://mlsanity.com/paper/1811.04655/) (2018)
- [Understanding who uses Reddit: Profiling individuals with a self-reported bipolar disorder diagnosis](https://mlsanity.com/paper/2104.11612/) (2021)

## Built on by (most cited first, 5 of 5)

- [Survey and Experiments on Mental Disorder Detection via Social Media: From Large Language Models and RAG to Agents](https://mlsanity.com/paper/2504.02800/) (2025)
- [Protective Factor-Aware Dynamic Influence Learning for Suicide Risk Prediction on Social Media](https://mlsanity.com/paper/2507.10008/) (2025)
- [Mental Disorder Classification via Temporal Representation of Text](https://mlsanity.com/paper/2406.15470/) (2024)
- [A Dual-Prompting for Interpretable Mental Health Language Models](https://mlsanity.com/paper/2402.14854/) (2024)
- [Multi-Agent Causal Reasoning for Suicide Ideation Detection Through Online Conversations](https://mlsanity.com/paper/2602.23577/) (2026)

## Abstract (arXiv)

Bipolar disorder (BD) is closely associated with an increased risk of suicide. However, while the prior work has revealed valuable insight into understanding the behavior of BD patients on social media, little attention has been paid to developing a model that can predict the future suicidality of a BD patient. Therefore, this study proposes a multi-task learning model for predicting the future suicidality of BD patients by jointly learning current symptoms. We build a novel BD dataset clinically validated by psychiatrists, including 14 years of posts on bipolar-related subreddits written by 818 BD patients, along with the annotations of future suicidality and BD symptoms. We also suggest a temporal symptom-aware attention mechanism to determine which symptoms are the most influential for predicting future suicidality over time through a sequence of BD posts. Our experiments demonstrate that the proposed model outperforms the state-of-the-art models in both BD symptom identification and future suicidality prediction tasks. In addition, the proposed temporal symptom-aware attention provides interpretable attention weights, helping clinicians to apprehend BD patients more comprehensively and to provide timely intervention by tracking mental state progression.