Papers with suicidal ideation
The Colorful Future of LLMs: Evaluating and Improving LLMs as Emotional Supporters for Queer Youth (2024.naacl-long)
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Shir Lissak, Nitay Calderon, Geva Shenkman, Yaakov Ophir, Eyal Fruchter, Anat Brunstein Klomek, Roi Reichart
| Challenge: | Queer youth face increased mental health risks, such as depression, anxiety, and suicidal ideation. |
| Approach: | They propose a scale that is inspired by psychological standards and expert input to evaluate LLM's interactions with queer-related content. |
| Outcome: | The proposed scale outperforms human responses to queer-related content and outperformed LLMs in the qualitative and quantitative analysis. |
Weakly-Supervised Methods for Suicide Risk Assessment: Role of Related Domains (2021.acl-short)
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| Challenge: | Among social media platforms, Reddit has emerged as the most promising one due to its anonymity and its focus on topic-based communities (subreddits) . a challenge for previous work on suicide risk assessment has been the small amount of labeled data. |
| Approach: | They propose to use social media to collect user data from r/SuicideWatch subreddit and annotate it with user-level suicide risk: no-risk, low-risk and high-risk. |
| Outcome: | The proposed model improves by using pseudo-labeling based on related issues around mental health (e.g., anxiety, depression) |
Suicide Ideation Detection via Social and Temporal User Representations using Hyperbolic Learning (2021.naacl-main)
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| Challenge: | Recent studies indicate that individuals exhibiting suicidal ideation increasingly turn to social media rather than mental health practitioners. |
| Approach: | They propose a framework leveraging a user’s emotional history and social information from a users neighborhood in a network to contextualize the interpretation of the latest tweet of a Twitter user. |
| Outcome: | The proposed framework outperforms state-of-the-art methods on this task, showing the benefits of both socially and personally contextualized representations. |
Cross-Lingual Suicidal-Oriented Word Embedding toward Suicide Prevention (2020.findings-emnlp)
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| Challenge: | Existing suicide dictionaries for other languages have been limited to Korean . a model that uses social media data to identify whether a post includes suicidal ideation is useful . |
| Approach: | They propose a model that uses existing suicide dictionaries for Korean to predict suicidal ideation . they use the existing dictionary for English and Chinese to translate a post into English and then use the separate suicide-oriented embeddings for English. |
| Outcome: | The proposed model can detect whether a given social media post includes suicidal ideation in Korean . it uses existing suicide dictionaries for other languages to translate the post into English and Chinese, and then embeds the suicide-oriented embeddings for English and China. |
PHASE: Learning Emotional Phase-aware Representations for Suicide Ideation Detection on Social Media (2021.eacl-main)
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| Challenge: | Recent studies indicate that individuals exhibiting suicidal ideation increasingly turn to social media rather than mental health practitioners. |
| Approach: | They propose a time-and-phase-aware framework that adaptively learns features from a user’s historical emotional spectrum to contextualize suicidal intent. |
| Outcome: | The proposed framework outperforms state-of-the-art methods while outperforming existing methods. |
Lexicography Saves Lives (LSL): Automatically Translating Suicide-Related Language (2025.coling-main)
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| Challenge: | Recent years have seen a marked increase in research that aims to identify or predict risk, intention or ideation of suicide in the context of Western culture. |
| Approach: | They propose to translate an existing dictionary related to suicide into 200 different languages and conduct human evaluations on a subset of translated dictionaries. |
| Outcome: | The proposed project aims to identify or predict risk, intention or ideation of suicide in the context of Western culture and reduce suicide rate by 2030 is one of the UN’s Sustainable Development Goals. |
MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare (2022.lrec-1)
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| Challenge: | Existing pretrained language models for mental health detection are inadequate . one in four people worldwide suffers from mental disorders . |
| Approach: | They train and release two pretrained masked language models to benefit machine learning for mental healthcare research . they demonstrate that language representations pretrained in the target domain improve the performance of mental health detection tasks. |
| Outcome: | The proposed models improve mental health detection tasks on several benchmarks and are available for free. |
If Eleanor Rigby Had Met ChatGPT: A Study on Loneliness in a Post-LLM World (2025.acl-long)
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| Challenge: | Loneliness is a global health concern and is prevalent worldwide . |
| Approach: | They analysed user interactions with ChatGPT outside of its marketed use as a task-oriented assistant and found that LLMs are more prevalent and riskier than LLM-based services . |
| Outcome: | The proposed models modify the LLMs to respond to loneliness and provide better engagement in conversations. |