Literature DB >> 27693129

Data Mining of Web-Based Documents on Social Networking Sites That Included Suicide-Related Words Among Korean Adolescents.

Juyoung Song1, Tae Min Song2, Dong-Chul Seo3, Jae Hyun Jin2.   

Abstract

PURPOSE: To investigate online search activity of suicide-related words in South Korean adolescents through data mining of social media Web sites as the suicide rate in South Korea is one of the highest in the world.
METHODS: Out of more than 2.35 billion posts for 2 years from January 1, 2011 to December 31, 2012 on 163 social media Web sites in South Korea, 99,693 suicide-related documents were retrieved by Crawler and analyzed using text mining and opinion mining. These data were further combined with monthly employment rate, monthly rental prices index, monthly youth suicide rate, and monthly number of reported bully victims to fit multilevel models as well as structural equation models.
RESULTS: The link from grade pressure to suicide risk showed the largest standardized path coefficient (beta = .357, p < .001) in structural models and a significant random effect (p < .01) in multilevel models. Depression was a partial mediator between suicide risk and grade pressure, low body image, victims of bullying, and concerns about disease. The largest total effect was observed in the grade pressure to depression to suicide risk. The multilevel models indicate about 27% of the variance in the daily suicide-related word search activity is explained by month-to-month variations. A lower employment rate, a higher rental prices index, and more bullying were associated with an increased suicide-related word search activity.
CONCLUSIONS: Academic pressure appears to be the biggest contributor to Korean adolescents' suicide risk. Real-time suicide-related word search activity monitoring and response system needs to be developed.
Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Adolescent health; Data mining; Social big data; Suicide

Mesh:

Year:  2016        PMID: 27693129     DOI: 10.1016/j.jadohealth.2016.07.025

Source DB:  PubMed          Journal:  J Adolesc Health        ISSN: 1054-139X            Impact factor:   5.012


  6 in total

Review 1.  Distress, Suicidality, and Affective Disorders at the Time of Social Networks.

Authors:  Charles-Edouard Notredame; M Morgiève; F Morel; S Berrouiguet; J Azé; G Vaiva
Journal:  Curr Psychiatry Rep       Date:  2019-09-14       Impact factor: 5.285

Review 2.  Secondary Use of Recorded or Self-expressed Personal Data: Consumer Health Informatics and Education in the Era of Social Media and Health Apps.

Authors:  P Staccini; L Fernandez-Luque
Journal:  Yearb Med Inform       Date:  2017-09-11

3.  Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea.

Authors:  Hayoung Kim; Yoonsun Han; Juyoung Song; Tae Min Song
Journal:  Int J Environ Res Public Health       Date:  2019-07-21       Impact factor: 3.390

4.  Health Information Needs of Young Chinese People Based on an Online Health Community: Topic and Statistical Analysis.

Authors:  Jie Wang; Xin Wang; Lei Wang; Yan Peng
Journal:  JMIR Med Inform       Date:  2021-11-08

Review 5.  Using Machine Learning for Pharmacovigilance: A Systematic Review.

Authors:  Patrick Pilipiec; Marcus Liwicki; András Bota
Journal:  Pharmaceutics       Date:  2022-01-23       Impact factor: 6.321

6.  Social Media Use and Deliberate Self-Harm Among Youth: A Systematized Narrative Review.

Authors:  Candice Biernesser; Craig J R Sewall; David Brent; Todd Bear; Christina Mair; Jeanette Trauth
Journal:  Child Youth Serv Rev       Date:  2020-05-29
  6 in total

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