社会大数据在识别韩国校园欺凌形式趋势中的应用。
Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea.
机构信息
Department of Child Psychology and Education, Sungkyunkwan University, Seoul 03063, Korea.
Department of Social Welfare, Seoul National University, Seoul 08826, Korea.
出版信息
Int J Environ Res Public Health. 2019 Jul 21;16(14):2596. doi: 10.3390/ijerph16142596.
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.
随着校园欺凌这一当代现象在韩国青少年中变得更加普遍、多样和频繁，社会大数据可能为理解数字时代校园欺凌趋势提供一种新的方法论范式。本研究通过提取词频-逆文档频率（TF-IDF）和未来信号，对 177 种校园欺凌形式进行分析，从而了解 436508 篇网络文档中 13 年 1 月 1 日至 17 年 12 月 31 日期间青少年的当前和未来欺凌经历。在社会大数据中，性欺凌迅速增加，而身体和网络欺凌则具有高频和高增长率。“群体攻击”和“性骚扰”等校园欺凌形式表现为微弱信号，而“网络欺凌”则是一个强烈信号。对包括言语、身体、关系、性和网络欺凌在内的五种校园欺凌形式的研究结果，对于深入了解这一日益严重的校园欺凌现象具有重要价值。
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