Literature DB >> 30809836

Mining social networks to improve suicide prevention: A scoping review.

Jorge Lopez-Castroman1,2,3, Bilel Moulahi3,4, Jérôme Azé3,4, Sandra Bringay3,4,5, Julie Deninotti2, Sebastien Guillaume1,3,6, Enrique Baca-Garcia7,8,9,10,11,12,13.   

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.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  mood disorders; natural language processing; social networks; suicidal behavior

Mesh:

Year:  2019        PMID: 30809836     DOI: 10.1002/jnr.24404

Source DB:  PubMed          Journal:  J Neurosci Res        ISSN: 0360-4012            Impact factor:   4.164


  3 in total

Review 1.  Spontaneously generated online patient experience data - how and why is it being used in health research: an umbrella scoping review.

Authors:  Julia Walsh; Christine Dwumfour; Jonathan Cave; Frances Griffiths
Journal:  BMC Med Res Methodol       Date:  2022-05-14       Impact factor: 4.612

2.  Risk Factors for Serious Suicide Attempts: Difference Between Older and Younger Attempters in the Emergency Department.

Authors:  Dong Wook Kim; Seo Eun Cho; Jae Myeong Kang; Soo Kyun Woo; Seung-Gul Kang; Byeong Kil Yeon; Seong-Jin Cho
Journal:  Front Psychiatry       Date:  2021-01-08       Impact factor: 4.157

3.  Deep cascaded multitask framework for detection of temporal orientation, sentiment and emotion from suicide notes.

Authors:  Soumitra Ghosh; Asif Ekbal; Pushpak Bhattacharyya
Journal:  Sci Rep       Date:  2022-03-15       Impact factor: 4.379

  3 in total

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