Building and Using Personal Knowledge Graph to Improve Suicidal Ideation Detection on Social Media

• URL: http://arxiv.org/abs/2012.09123v1
• Date: Wed, 16 Dec 2020 18:09:32 GMT
• Title: Building and Using Personal Knowledge Graph to Improve Suicidal Ideation Detection on Social Media
• Authors: Lei Cao, Huijun Zhang, and Ling Feng
• Abstract summary: We build and unify a high-level suicide-oriented knowledge graph with deep neural networks for suicidal ideation detection on social media. We show that the social media-based suicidal ideation detection can achieve over 93% accuracy. Under these categories, posted text, stress level, stress duration, posted image, and ruminant thinking contribute to one's suicidal ideation detection.
• Score: 4.769234388745917
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: A large number of individuals are suffering from suicidal ideation in the world. There are a number of causes behind why an individual might suffer from suicidal ideation. As the most popular platform for self-expression, emotion release, and personal interaction, individuals may exhibit a number of symptoms of suicidal ideation on social media. Nevertheless, challenges from both data and knowledge aspects remain as obstacles, constraining the social media-based detection performance. Data implicitness and sparsity make it difficult to discover the inner true intentions of individuals based on their posts. Inspired by psychological studies, we build and unify a high-level suicide-oriented knowledge graph with deep neural networks for suicidal ideation detection on social media. We further design a two-layered attention mechanism to explicitly reason and establish key risk factors to individual's suicidal ideation. The performance study on microblog and Reddit shows that: 1) with the constructed personal knowledge graph, the social media-based suicidal ideation detection can achieve over 93% accuracy; and 2) among the six categories of personal factors, post, personality, and experience are the top-3 key indicators. Under these categories, posted text, stress level, stress duration, posted image, and ruminant thinking contribute to one's suicidal ideation detection.

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