A Novel Method for Suicidal Thought Detection

Abstract

Suicide is a critical issue in modern society. Early detection and prevention of suicide attempts should be addressed to save people’s life. Current suicidal thought detection methods include clinical methods based on the interaction between social workers or experts and the targeted individuals and machine learning techniques with feature engineering or deep learning for automatic detection based on online social contents.  In this paper, we propose a methodology based on experimental research for building a suicidal ideation detection system using publicly available Reddit datasets, word-embedding approaches, such as TF-IDF and Word2Vec, for text representation, and hybrid deep learning and machine learning algorithms for classification.