The Journal of Information Systems (한국정보시스템학회지:정보시스템연구)

Korea Association of Information Systems (한국정보시스템학회)
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Juvenile Cyber Deviance Factors and Predictive Model Development Using a Mixed Method Approach

사이버비행 요인 파악 및 예측모델 개발: 혼합방법론 접근

  • Received : 2021.04.12
  • Accepted : 2021.05.27
  • Published : 2021.06.30
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Abstract

Purpose Cyber deviance of adolescents has become a serious social problem. With a widespread use of smartphones, incidents of cyber deviance have increased in Korea and both quantitative and qualitative damages such as suicide and depression are increasing. Research has been conducted to understand diverse factors that explain adolescents' delinquency in cyber space. However, most previous studies have focused on a single theory or perspective. Therefore, this study aims to comprehensively analyze motivations of juvenile cyber deviance and to develop a predictive model for delinquent adolescents by integrating four different theories on cyber deviance. Design/methodology/approach By using data from Korean Children & Youth Panel Survey 2010, this study extracts 27 potential factors for cyber deivance based on four background theories including general strain, social learning, social bonding, and routine activity theories. Then this study employs econometric analysis to empirically assess the impact of potential factors and utilizes a machine learning approach to predict the likelihood of cyber deviance by adolescents. Findings This study found that general strain factors as well as social learning factors have positive effects on cyber deviance. Routine activity-related factors such as real-life delinquent behaviors and online activities also positively influence the likelihood of cyber diviance. On the other hand, social bonding factors such as community commitment and attachment to community lessen the likelihood of cyber deviance while social factors related to school activities are found to have positive impacts on cyber deviance. This study also found a predictive model using a deep learning algorithm indicates the highest prediction performance. This study contributes to the prevention of cyber deviance of teenagers in practice by understanding motivations for adolescents' delinquency and predicting potential cyber deviants.

Keywords

Acknowledgement

이 논문은 2018년 대한민국 교육부와 한국연구재단의 지원을 받아 수행된 연구임 (NRF-2018S1A3A2075114)

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