Mining social networks to improve suicide prevention: A scoping review. Issue 4 (27th February 2019)

• Record Type: Journal Article
• Authors: Lopez‐Castroman, Jorge; Moulahi, Bilel; Azé, Jérôme; Bringay, Sandra; Deninotti, Julie; Guillaume, Sebastien; Baca‐Garcia, Enrique
• Other Names: Courtet Philippe guestEditor.
• Is Part Of: Journal of neuroscience research. Volume 98:Issue 4(2020)
• Page Start: 616
• Page End: 625
• Publication Date: 2019-02-27
• Subjects: mood disorders -- natural language processing -- social networks -- suicidal behavior; Neurobiology -- Periodicals; 612
• DOI: 10.1002/jnr.24404
• Languages: English
• ISSNs: 0360-4012

Abstract

Abstract: Attention about the risks of online social networks (SNs) has been called upon reports describing their use to express emotional distress and suicidal ideation or plans. On the Internet, cyberbullying, suicide pacts, Internet addiction, and "extreme" communities seem to increase suicidal behavior (SB). In this study, the scientific literature about SBs and SNs was narratively reviewed. Some authors focus on detecting at‐risk populations through data mining, identification of risks factors, and web activity patterns. Others describe prevention practices on the Internet, such as websites, screening, and applications. Targeted interventions through SNs are also contemplated when suicidal ideation is present. Multiple predictive models should be defined, implemented, tested, and combined in order to deal with the risk of SB through an effective decision support system. This endeavor might require a reorganization of care for SNs users presenting suicidal ideation.