Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications
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 ideation 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. This paper is the first survey that comprehensively introduces and discusses the methods from these categories. Domain-specific applications of suicidal ideation detection are reviewed according to their data sources, i.e., questionnaires, electronic health records, suicide notes, and online user content. Several specific tasks and datasets are introduced and summarized to facilitate further research. Finally, we summarize the limitations of current work and provide an outlook of further research directions.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningFeature EngineeringSimilar Papers 제목 키워드 기반
Suicidal Ideation Detection on Social Media: A Review of Machine Learning Methods
Social media platforms have transformed traditional communication methods by allowing users worldwide to communicate instantly, openly, and frequently. People use social media to express their opinion and share their per…
BIG-bench Machine Learningtext-classificationText ClassificationExploring and Learning Suicidal Ideation Connotations on Social Media with Deep Learning
The increasing suicide rates amongst youth and its high correlation with suicidal ideation expression on social media warrants a deeper investigation into models for the detection of suicidal intent in text such as tweet…
ClassificationDeep LearningGeneral ClassificationSentence+3Detecting Suicidal Ideation in Chinese Microblogs with Psychological Lexicons
Suicide is among the leading causes of death in China. However, technical approaches toward preventing suicide are challenging and remaining under development. Recently, several actual suicidal cases were preceded by use…
BIG-bench Machine LearningBuilding and Using Personal Knowledge Graph to Improve Suicidal Ideation Detection on Social Media
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…
A self attention TCN based model for suicidal ideation detection from social media posts
Early suicidal ideation detection has long been regarded as an important task that can benefit both society and individuals. In this regard, it has been shown that, very frequently, the first symptoms of this problem can…