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

Hayoung Kim Donnelly, Yoonsun Han, Juyoung Song and Tae Min Song
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Hayoung Kim Donnelly: Department of Child Psychology and Education, Sungkyunkwan University, Seoul 03063, Korea
Yoonsun Han: Department of Social Welfare, Seoul National University, Seoul 08826, Korea
Juyoung Song: Department of Administration of Justice, Pennsylvania State University, Schuylkill Haven, PA 17972, USA
Tae Min Song: Department of Health Management, Sahmyook University, Seoul 01795, Korea

IJERPH, 2019, vol. 16, issue 14, 1-12

Abstract: 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.

Keywords: school bullying forms; social big data; TF-IDF; Future Signals; South Korea (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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