Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Analysing the connectivity and communication of suicidal users on Twitter

Colombo, Gualtiero B., Burnap, Peter ORCID:, Hodorog, Andrei ORCID: and Scourfield, Jonathan Bryn ORCID: 2015. Analysing the connectivity and communication of suicidal users on Twitter. Computer Communications 73 (B) , pp. 291-300. 10.1016/j.comcom.2015.07.018

[thumbnail of Colombo et al., 2015.pdf]
PDF - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (2MB) | Preview


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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Social Sciences (Includes Criminology and Education)
Subjects: H Social Sciences > HM Sociology
Q Science > QA Mathematics > QA76 Computer software
Uncontrolled Keywords: Social media; Social network analysis; Twitter; Computational social science; Suicide
Publisher: Elsevier
ISSN: 0140-3664
Funders: Department of Health Policy Research Programme
Date of First Compliant Deposit: 30 March 2016
Date of Acceptance: 15 July 2015
Last Modified: 03 May 2023 17:48

Citation Data

Cited 90 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics