Machine learning for suicidal ideation identification: A systematic literature review
作者：
Highlights：
• Suicidal ideation is the first stage in the risk scale, being a potential gate for suicide prevention.
• Studies explored mainly data from social media and investigated suicidal tendencies in the individuals' language.
• Deep learning models seem to be a tendency in this area nowadays, mainly when the task is text analysis.
• This review found a growing interest in suicidal ideation in the last years.
• This study summarizes machine learning techniques and current research challenges into two taxonomies.
摘要
•Suicidal ideation is the first stage in the risk scale, being a potential gate for suicide prevention.•Studies explored mainly data from social media and investigated suicidal tendencies in the individuals' language.•Deep learning models seem to be a tendency in this area nowadays, mainly when the task is text analysis.•This review found a growing interest in suicidal ideation in the last years.•This study summarizes machine learning techniques and current research challenges into two taxonomies.
论文关键词：Machine learning,Suicidal ideation identification,Suicide prevention,Mental health,Systematic literature review
论文评审过程：Received 15 April 2021, Revised 2 November 2021, Accepted 10 November 2021, Available online 12 November 2021, Version of Record 23 December 2021.
论文官网地址：https://doi.org/10.1016/j.chb.2021.107095
