Articlehybrid2015

Analysing the connectivity and communication of suicidal users on twitter

Gualtiero B. Colombo · Pete Burnap · Andrei Hodorog · Jonathan Scourfield

141 citations0/0 files storedComputer Communications

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Mental Health via Writing Suicide and Self-Harm Studies Complex Network Analysis Techniques

Abstract

In this paper we aim to understand the connectivity and communication characteristics of Twitter users who post content subsequently classified by human annotators as containing possible suicidal intent or thinking, commonly referred to as suicidal ideation. We achieve this understanding by analysing the characteristics of their social networks. Starting from a set of human annotated Tweets we retrieved the authors' followers and friends lists, and identified users who retweeted the suicidal content. We subsequently built the social network graphs. Our results show a high degree of reciprocal connectivity between the authors of suicidal content when compared to other studies of Twitter users, suggesting a tightly-coupled virtual community. In addition, an analysis of the retweet graph has identified bridge nodes and hub nodes connecting users posting suicidal ideation with users who were not, thus suggesting a potential for information cascade and risk of a possible contagion effect. This is particularly emphasised by considering the combined graph merging friendship and retweeting links.

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References

1973The Strength of Weak Ties 2002In Defense of the Internet: The Relationship between Internet Communication and Depression, Loneliness, Self-Esteem, and Perceived Social Support 2004Suicide and Friendships Among American Adolescents 2011Feeling bad on Facebook: depression disclosures by college students on a social networking site 1996A prospective study of social networks in relation to total mortality and cardiovascular disease in men in the USA.2003Media Contagion and Suicide Among the Young 2013The Power of the Web: A Systematic Review of Studies of the Influence of the Internet on Self-Harm and Suicide in Young People 2001Suicide and the Media

Cited by

2017Multi-class machine classification of suicide-related communication on Twitter 2018Exploring and Learning Suicidal Ideation Connotations on Social Media with Deep Learning 2022A Comparative Analysis on Suicidal Ideation Detection Using NLP, Machine, and Deep Learning 2020Detection of Suicidal Ideation on Social Media: Multimodal, Relational, and Behavioral Analysis 2017Tweeting celebrity suicides: Users' reaction to prominent suicide deaths on Twitter and subsequent increases in actual suicides

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