阿拉伯网络欺凌检测使用机器学习:现状的艺术调查

Norah Alsunaidi, Sarah Aljbali, Y. Yasin, Hamoud Aljamaan
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引用次数: 0

摘要

网络欺凌(CB)是一个全球性的难题,它正在迅速发展,影响到包括未成年人在内的更多个人。CB的破坏性后果表明,迫切需要规范不道德或非法用户的在线行为。大量研究人员试图利用机器学习的潜力来检测和预防这种有害行为,然而,针对阿拉伯语内容的现有研究仍在兴起。因此,本文对已发表的基于阿拉伯语内容的CB检测实证研究进行了全面回顾,重点是适应的方法、差距和挑战。我们希望这项工作能够支持CB检测领域的研究人员,以营造一个安全的在线环境,并保护用户免受CB的任何有害后果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Arabic Cyberbullying Detection Using Machine Learning: State of the Art Survey
Cyberbullying (CB) is a global dilemma that is growing rapidly to affect more individuals including minors. The devastating consequences of CB indicate a pressing necessity to regulate unethical or illegal users' online behaviors. A remarkable number of researchers attempted to harness the potential of machine learning to detect and prevent such harmful behaviors, however, the existing studies targeting Arabic-based content are still emerging. Therefore, this paper provides a comprehensive review of the published empirical studies in CB detection in Arabic-based content with an emphasis on the adapted methodologies, gaps, and challenges. We hope this work would support researchers in the area of CB-detection to foster a safe online environment and protect against any harmful consequences of CB among users.
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