The reviewed record of science sign in
Pith

arxiv: 2401.01023 · v1 · pith:VQ6FN5QY · submitted 2024-01-02 · cs.HC · cs.LG

CautionSuicide: A Deep Learning Based Approach for Detecting Suicidal Ideation in Real Time Chatbot Conversation

Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 kernel pith:VQ6FN5QYrecord.jsonopen to challenge →

classification cs.HC cs.LG
keywords ideationssuicidalsuicidechatbotsdeepdetectiondigitalproposed
0
0 comments X
read the original abstract

Suicide is recognized as one of the most serious concerns in the modern society. Suicide causes tragedy that affects countries, communities, and families. There are many factors that lead to suicidal ideations. Early detection of suicidal ideations can help to prevent suicide occurrence by providing the victim with the required professional support, especially when the victim does not recognize the danger of having suicidal ideations. As technology usage has increased, people share and express their ideations digitally via social media, chatbots, and other digital platforms. In this paper, we proposed a novel, simple deep learning-based model to detect suicidal ideations in digital content, mainly focusing on chatbots as the primary data source. In addition, we provide a framework that employs the proposed suicide detection integration with a chatbot-based support system.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.