Meta-analysis of Predictors of School Violence Offense and School Violence Victimized Experience

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

Kim

Han

Song

et al. 2019

IJERPH

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Meta-analysis of Predictors of School Violence Offense and School Violence Victimized Experience

Cited by 1 publication

References 3 publications

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

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

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