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Mining social networks to improve suicide prevention: A scoping review |
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| Authors: | Jorge Lopez-Castroman Bilel Moulahi Jérôme Azé Sandra Bringay Julie Deninotti Sebastien Guillaume Enrique Baca-Garcia |
| Institution: | 1. INSERM U888, La Colombière Hospital, Montpellier, France;2. Departments of Psychiatry, Media and Internet, and Telecommunication and Networks, University of Montpellier UM, Montpellier, France
LIRMM UMR 5506, Montpellier, France;3. Departments of Psychiatry, Media and Internet, and Telecommunication and Networks, University of Montpellier UM, Montpellier, France LIRMM UMR 5506, Montpellier, France Department of Applied Mathematics and Informatics, Paul-Valery University, Montpellier, France;4. Department of Adult Psychiatry, CHRU Nimes, Nimes, France;5. INSERM U888, La Colombière Hospital, Montpellier, France Departments of Psychiatry, Media and Internet, and Telecommunication and Networks, University of Montpellier UM, Montpellier, France Department of Emergency Psychiatry and Post-Acute Care, Montpellier University Hospital, Montpellier, France;6. Department of Psychiatry, Fundacion Jimenez Diaz University Hospital, Madrid, Spain Department of Psychiatry, University Hospital Rey Juan Carlos, Mostoles, Spain Department of Psychiatry, General Hospital of Villalba, Madrid, Spain Department of Psychiatry, University Hospital Infanta Elena, Valdemoro, Spain Department of Psychiatry, Madrid Autonomous University, Madrid, Spain CIBERSAM (Centro de Investigacion en Salud Mental), Carlos III Institute of Health, Madrid, Spain Universidad Catolica del Maule, Talca, Chile |
| 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. |
| Keywords: | mood disorders natural language processing social networks suicidal behavior |