Tree hole rescue: an AI approach for suicide risk detection and online suicide intervention.

IF 5.4 3区 材料科学 Q2 CHEMISTRY, PHYSICAL
ACS Applied Energy Materials Pub Date : 2024-09-03 eCollection Date: 2024-12-01 DOI:10.1007/s13755-024-00298-3
Zhisheng Huang, Qing Hu
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引用次数: 0

Abstract

Adolescent suicide has become an important social issue of general concern. Many young people express their suicidal feelings and intentions through online social media, e.g., Twitter, Microblog. The "tree hole" is the Chinese name for places on the Web where people post secrets. It provides the possibility of using Artificial Intelligence and big data technology to detect the posts where someone express the suicidal signal from those "tree hole" social media. We have developed the Web-based intelligent agents (i.e., AI-based programs) which can monitor the "tree hole" websites in Microblog every day by using knowledge graph technology. We have organized Tree-hole Rescue Team, which consists of more than 1000 volunteers, to carry out suicide rescue intervention according to the daily monitoring notifications. From 2018 to 2023, Tree-hole Rescue Team has prevented more than 6600 suicides. A few thousands of people have been saved within those 6 years. In this paper, we present the basic technology of Web-based Tree Hole intelligent agents and elaborate how the intelligent agents can discover suicide attempts and issue corresponding monitoring notifications and how the volunteers of Tree Hole Rescue Team can conduct online suicide intervention. This research also shows that the knowledge graph approach can be used for the semantic analysis on social media.

树洞救援:一种用于自杀风险检测和在线自杀干预的人工智能方法。
青少年自杀已成为人们普遍关注的重要社会问题。许多青少年通过网络社交媒体,如微博、微信等,表达自己的自杀情绪和意向。树洞 "是网络上人们发布秘密的地方的中文名称。这为利用人工智能和大数据技术从这些 "树洞 "社交媒体中检测出有人表达自杀信号的帖子提供了可能。我们开发了基于网络的智能代理(即基于人工智能的程序),利用知识图谱技术每天监测微博中的 "树洞 "网站。我们组织了由 1000 多名志愿者组成的 "树洞救援队",根据每天的监测通知进行自杀救援干预。从 2018 年到 2023 年,树洞救援队已经阻止了 6600 多起自杀事件。在这 6 年中,有数千人被拯救。本文介绍了基于网络的树洞智能代理的基本技术,阐述了智能代理如何发现自杀企图并发出相应的监测通知,以及树洞救援队的志愿者如何进行在线自杀干预。这项研究还表明,知识图谱方法可用于社交媒体的语义分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Energy Materials
ACS Applied Energy Materials Materials Science-Materials Chemistry
CiteScore
10.30
自引率
6.20%
发文量
1368
期刊介绍: ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.
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