How Social Media Big Data Can Improve Suicide Prevention

TL;DR

This study uses supercomputing to analyze social media data, revealing extensive engagement with suicide-related content among young adults, highlighting the need for targeted prevention strategies on social platforms.

Contribution

It provides the first large-scale, high-performance analysis of social media users engaged with suicide-related content, offering insights for public health interventions.

Findings

Over 570,000 users engaged with suicide-related content

Most users were aged 21-24, with a higher female representation

Users were involved in up to 15 suicide-related groups

Abstract

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.