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Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea
As the contemporary phenomenon of school bullying has become more widespread, diverse, and frequent among adolescents in Korea, social big data may offer a new methodological paradigm for understanding the trends of school bullying in the digital era. This study identified Term Frequency-Inverse Doc...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678225/ https://www.ncbi.nlm.nih.gov/pubmed/31330879 http://dx.doi.org/10.3390/ijerph16142596 |
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author | Kim, Hayoung Han, Yoonsun Song, Juyoung Song, Tae Min |
author_facet | Kim, Hayoung Han, Yoonsun Song, Juyoung Song, Tae Min |
author_sort | Kim, Hayoung |
collection | PubMed |
description | As the contemporary phenomenon of school bullying has become more widespread, diverse, and frequent among adolescents in Korea, social big data may offer a new methodological paradigm for understanding the trends of school bullying in the digital era. This study identified Term Frequency-Inverse Document Frequency (TF-IDF) and Future Signals of 177 school bullying forms to understand the current and future bullying experiences of adolescents from 436,508 web documents collected between 1 January 2013, and 31 December 2017. In social big data, sexual bullying rapidly increased, and physical and cyber bullying had high frequency with a high rate of growth. School bullying forms, such as “group assault” and “sexual harassment”, appeared as Weak Signals, and “cyber bullying” was a Strong Signal. Findings considering five school bullying forms (verbal, physical, relational, sexual, and cyber bullying) are valuable for developing insights into the burgeoning phenomenon of school bullying. |
format | Online Article Text |
id | pubmed-6678225 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66782252019-08-19 Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea Kim, Hayoung Han, Yoonsun Song, Juyoung Song, Tae Min Int J Environ Res Public Health Article As the contemporary phenomenon of school bullying has become more widespread, diverse, and frequent among adolescents in Korea, social big data may offer a new methodological paradigm for understanding the trends of school bullying in the digital era. This study identified Term Frequency-Inverse Document Frequency (TF-IDF) and Future Signals of 177 school bullying forms to understand the current and future bullying experiences of adolescents from 436,508 web documents collected between 1 January 2013, and 31 December 2017. In social big data, sexual bullying rapidly increased, and physical and cyber bullying had high frequency with a high rate of growth. School bullying forms, such as “group assault” and “sexual harassment”, appeared as Weak Signals, and “cyber bullying” was a Strong Signal. Findings considering five school bullying forms (verbal, physical, relational, sexual, and cyber bullying) are valuable for developing insights into the burgeoning phenomenon of school bullying. MDPI 2019-07-21 2019-07 /pmc/articles/PMC6678225/ /pubmed/31330879 http://dx.doi.org/10.3390/ijerph16142596 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kim, Hayoung Han, Yoonsun Song, Juyoung Song, Tae Min Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea |
title | Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea |
title_full | Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea |
title_fullStr | Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea |
title_full_unstemmed | Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea |
title_short | Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea |
title_sort | application of social big data to identify trends of school bullying forms in south korea |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678225/ https://www.ncbi.nlm.nih.gov/pubmed/31330879 http://dx.doi.org/10.3390/ijerph16142596 |
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