{"title":"分类和评估方面的自杀意念检测方法:一个系统的回顾","authors":"Golnaz Nikmehr , Aritz Bilbao-Jayo , Aitor Almeida","doi":"10.1016/j.chbr.2025.100733","DOIUrl":null,"url":null,"abstract":"<div><div>Suicide remains a critical global issue and one of the leading causes of death worldwide. As this problem grows, the need for effective prevention strategies becomes increasingly urgent. Social networks and online platforms, such as Twitter, have emerged as spaces where people openly share their thoughts and emotions, including negative feelings, reflections on life, and even suicidal thoughts. This makes social media data an important resource for efforts to detect and reduce the risk of suicide.</div><div>This systematic review examines 92 studies published between 2018 and 2024 on the detection of suicidal ideation. The studies are categorized using a multidimensional framework that considers three key aspects: the platforms used for data collection, the analytical techniques applied, and the specific features employed to identify suicidal ideation.</div><div>By exploring these dimensions, the review highlights existing gaps and limitations in current methods, offering insights to guide future research and improve strategies for suicide prevention.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"19 ","pages":"Article 100733"},"PeriodicalIF":5.8000,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Categorizing and assessing aspects of suicidal ideation detection approaches: A systematic review\",\"authors\":\"Golnaz Nikmehr , Aritz Bilbao-Jayo , Aitor Almeida\",\"doi\":\"10.1016/j.chbr.2025.100733\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Suicide remains a critical global issue and one of the leading causes of death worldwide. As this problem grows, the need for effective prevention strategies becomes increasingly urgent. Social networks and online platforms, such as Twitter, have emerged as spaces where people openly share their thoughts and emotions, including negative feelings, reflections on life, and even suicidal thoughts. This makes social media data an important resource for efforts to detect and reduce the risk of suicide.</div><div>This systematic review examines 92 studies published between 2018 and 2024 on the detection of suicidal ideation. The studies are categorized using a multidimensional framework that considers three key aspects: the platforms used for data collection, the analytical techniques applied, and the specific features employed to identify suicidal ideation.</div><div>By exploring these dimensions, the review highlights existing gaps and limitations in current methods, offering insights to guide future research and improve strategies for suicide prevention.</div></div>\",\"PeriodicalId\":72681,\"journal\":{\"name\":\"Computers in human behavior reports\",\"volume\":\"19 \",\"pages\":\"Article 100733\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2025-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers in human behavior reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2451958825001484\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in human behavior reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2451958825001484","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, EXPERIMENTAL","Score":null,"Total":0}
Categorizing and assessing aspects of suicidal ideation detection approaches: A systematic review
Suicide remains a critical global issue and one of the leading causes of death worldwide. As this problem grows, the need for effective prevention strategies becomes increasingly urgent. Social networks and online platforms, such as Twitter, have emerged as spaces where people openly share their thoughts and emotions, including negative feelings, reflections on life, and even suicidal thoughts. This makes social media data an important resource for efforts to detect and reduce the risk of suicide.
This systematic review examines 92 studies published between 2018 and 2024 on the detection of suicidal ideation. The studies are categorized using a multidimensional framework that considers three key aspects: the platforms used for data collection, the analytical techniques applied, and the specific features employed to identify suicidal ideation.
By exploring these dimensions, the review highlights existing gaps and limitations in current methods, offering insights to guide future research and improve strategies for suicide prevention.