How Social Media Big Data Can Improve Suicide Prevention

Fuente: arXiv
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Autori principali: Peshkovskaya, Anastasia, Xiang, Yu-Tao
Natura: Preprint
Pubblicazione: 2024
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author Peshkovskaya, Anastasia
Xiang, Yu-Tao
author_facet Peshkovskaya, Anastasia
Xiang, Yu-Tao
contents In the light of increasing clues on social media impact on self-harm and suicide risks, there is still no evidence on who are and how factually engaged in suicide-related online behaviors. This study reports new findings of high-performance supercomputing investigation of publicly accessible big data sourced from one of the world-largest social networking site. Three-month supercomputer searching resulted in 570,156 young adult users who consumed suicide-related information on social media. Most of them were 21-24 year olds with higher share of females (58%) of predominantly younger age. Every eight user was alarmingly engrossed with up to 15 suicide-related online groups. Evidently, suicide groups on social media are highly underrated public health issue that might weaken the prevention efforts. Suicide prevention strategies that target social media users must be implemented extensively. While major gap in functional understanding of technologies relevance for use in public mental health still exists, current findings act for better understanding digital technologies utility for translational advance and offer relevant evidence-based framework for improving suicide prevention in general population.
format Preprint
id arxiv_https___arxiv_org_abs_2401_07718
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle How Social Media Big Data Can Improve Suicide Prevention
Peshkovskaya, Anastasia
Xiang, Yu-Tao
Computers and Society
Human-Computer Interaction
Social and Information Networks
In the light of increasing clues on social media impact on self-harm and suicide risks, there is still no evidence on who are and how factually engaged in suicide-related online behaviors. This study reports new findings of high-performance supercomputing investigation of publicly accessible big data sourced from one of the world-largest social networking site. Three-month supercomputer searching resulted in 570,156 young adult users who consumed suicide-related information on social media. Most of them were 21-24 year olds with higher share of females (58%) of predominantly younger age. Every eight user was alarmingly engrossed with up to 15 suicide-related online groups. Evidently, suicide groups on social media are highly underrated public health issue that might weaken the prevention efforts. Suicide prevention strategies that target social media users must be implemented extensively. While major gap in functional understanding of technologies relevance for use in public mental health still exists, current findings act for better understanding digital technologies utility for translational advance and offer relevant evidence-based framework for improving suicide prevention in general population.
title How Social Media Big Data Can Improve Suicide Prevention
topic Computers and Society
Human-Computer Interaction
Social and Information Networks
url https://arxiv.org/abs/2401.07718