이건우, 김휘강,

Vol. 35, No. 3, pp. 659-679, 6월. 2025
10.13089/JKIISC.2025.35.3.659, Full Text:
Keywords: Survey, Online game, Cyberbullying, Detection
Abstract

Traditionally, cyber threats in the online game industry have primarily involved game bots and gold farming groups. The most significant threat is the use of automated game bots and their illegal financial gain by doing real money trading. Prior research has mainly focused on detecting game bots and unauthorized real money trading. However, with the growth of online games and the increased rich interactions among users within virtual game space, various forms of cyberbullying have emerged, including verbal abuse, sexual harassment, and the leakage of personal information. This study examines the types of cyberbullying that occur in online games and provides a theoretical analysis. Additionally, it reviews and categorizes research conducted over the past decade on detecting cyberbullying in online games based on data types, detection algorithms, and the data used. Furthermore, methods to mitigate cyberbullying are reviewed according to different approaches and integrated from a computational social science perspective. This study aims to provide future research directions for scholars investigating cyberbullying in online gaming.

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