Papers with detection of suicidal ideation

2 papers
Self-Adapted Utterance Selection for Suicidal Ideation Detection in Lifeline Conversations (2023.eacl-main)

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Challenge: Existing methods for identifying suicidal ideation in phone conversations are difficult to use because of their long duration and noisy nature.
Approach: They propose a self-adaptive approach that identifies the most critical utterances that the NLP model can more easily distinguish.
Outcome: The proposed approach outperforms the baseline models in overall performance with an F score of 66.01% and significantly higher F-score in detecting the most dangerous cases.
Latent Suicide Risk Detection on Microblog via Suicide-Oriented Word Embeddings and Layered Attention (D19-1)

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Challenge: Existing approaches to detect suicidal ideation on social media are limited to a small group of people.
Approach: They propose to use tree holes to embed words into microblogs to strengthen the sensibility of suicide-related lexicons and to use a two-layered attention mechanism to grasp intermittently changing points from individual's open blog streams.
Outcome: The proposed approach can achieve over 91% accuracy with the use of suicide-oriented word embeddings and attention on a large-scale well-labelled suicide data set.

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