Journal of Artificial Intelligence for Medical Sciences

Volume 2, Issue 1-2, June 2021, Pages 55 - 61

Temporal Aspects of Tree Hole Data

Authors
Zengzhen Du, Dan Xie, *, Min Hu
Hubei University of Chinese Medicine, Wuhan, Hubei, China
*Corresponding author. Email: dinaxie@hbtcm.edu.cn
Corresponding Author
Dan Xie
Received 9 December 2020, Accepted 1 June 2021, Available Online 9 June 2021.
DOI
https://doi.org/10.2991/jaims.d.210604.001How to use a DOI?
Keywords
Tree hole, Suicide assistance, Temporal aspects
Abstract

At present, adolescent suicide becomes a serious social problem. Many young people express suicidal thoughts through online social media. Weibo is a famous social media platform for real-time information sharing in China. When a Weibo user committed suicide, many other users continued to post information on this Weibo. Such a space is often called a “tree hole.” By analyzing the temporal aspects of tree hole data, we can understand the behavioral characteristics of suicide attempters and provide more valuable information for suicide assistance. This paper will introduce the analysis of temporal characteristics of tree hole data and guide suicide assistance through suicide monitoring and early warning based on these time characteristics.

Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Artificial Intelligence for Medical Sciences
Volume-Issue
2 - 1-2
Pages
55 - 61
Publication Date
2021/06
ISSN (Online)
2666-1470
DOI
https://doi.org/10.2991/jaims.d.210604.001How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Zengzhen Du
AU  - Dan Xie
AU  - Min Hu
PY  - 2021
DA  - 2021/06
TI  - Temporal Aspects of Tree Hole Data
JO  - Journal of Artificial Intelligence for Medical Sciences
SP  - 55
EP  - 61
VL  - 2
IS  - 1-2
SN  - 2666-1470
UR  - https://doi.org/10.2991/jaims.d.210604.001
DO  - https://doi.org/10.2991/jaims.d.210604.001
ID  - Du2021
ER  -