Assessing vulnerability to surges in suicide-related tweets using Japan census data: Case-only study

Background: As the use of social media becomes more widespread, its impact on health cannot be ignored. However, limited research has been conducted on the relationship between social media and suicide. Little is known about individuals’ vulnerable to suicide, especially when social media suicide information is extremely prevalent. Objective: This study aims to identify the […]

Tracking suicide risk factors through Twitter in the US

Background: Suicide is a leading cause of death in the United States. Social media such as Twitter is an emerging surveillance tool that may assist researchers in tracking suicide risk factors in real time. Aims: To identify suicide-related risk factors through Twitter conversations by matching on geographic suicide rates from vital statistics data. Method: At-risk tweets were filtered […]

Responses to a self-presented suicide attempt in social media: A social network analysis

Background: The self-presentation of suicidal acts in social media has become a public health concern. Aims: This article centers on a Chinese microblogger who posted a wrist-cutting picture that was widely circulated in Chinese social media in 2011. This exploratory study examines written reactions of a group of Chinese microbloggers exposed to the post containing a self-harming […]

Geospatial mapping of suicide-related tweets and sentiments among Malaysians during the COVID-19 pandemic

The government enacted the Movement Control Order (MCO) to curb the spread of the COVID-19 pandemic in Malaysia, restricting movement and shutting down several commercial enterprises around the nation. The crisis, which lasted over two years and featured a few MCOs, had an impact on Malaysians’ mental health. This study aimed to understand the context […]

Suicidal tweets detection in online social media using machine learning

This project describes content analysis of text with to identify suicidal tendencies and types. This article also describes how to make a sentence classifier that uses a neural network created using various libraries created for machine learning in the Python programming language. Attention is paid to the problem of teenage suicide and «groups of death» […]

The relationship between suicide-related Twitter events and suicides in Ontario from 2015-2016.

Background: Many studies have demonstrated suicide contagion through mainstream journalism; however, few have explored suicide-related social media events and their potential relationship to suicide deaths. Aims: To determine whether Twitter events were associated with changes in subsequent suicides. Methods: Suicide-related Twitter events that garnered at least 100 tweets originating in Ontario, Canada (July 1, 2015 to June 30, 2016) were […]

Tweet classification to assist human moderation for suicide prevention

Social media platforms are already engaged in leveraging existing online socio-technical systems to employ just-in-time interventions for suicide prevention to the public. These efforts primarily rely on self-reports of potential self-harm content that is reviewed by moderators. Most recently, platforms have employed automated models to identify self-harm content, but acknowledge that these automated models still […]

Detecting suicidality on Twitter.

Twitter is increasingly investigated as a means of detecting mental health status, including depression and suicidality, in the population. However, validated and reliable methods are not yet fully established. This study aimed to examine whether the level of concern for a suicide-related post on Twitter could be determined based solely on the content of the […]