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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...

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Detalles Bibliográficos
Autores principales: Kim, Hayoung, Han, Yoonsun, Song, Juyoung, Song, Tae Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
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.
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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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