基于亲子关系的网络欺凌检测

Ziyi Li, Junpei Kawamoto, Yaokai Feng, K. Sakurai
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引用次数: 12

摘要

网络欺凌是社交网络服务中的一个潜在问题,威胁着用户的身心健康。以前对自动网络欺凌检测的研究大多是基于文本或基于社交的方法。前一种方法通过内容内部的一组文本特征来识别网络欺凌内容,后一种方法通过围绕内容的社会信息来识别网络欺凌内容。由于每个内容都使用相同的特征进行评估,因此这些方法无法满足个人SNS用户的不同网络欺凌标准。因此,在本文中,我们提出了一种自动网络欺凌检测方法,利用评论之间的亲子关系来捕捉第三方的反应来检测网络欺凌评论。我们能够仅使用公开可用的数据来提高网络欺凌检测的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cyberbullying detection using parent-child relationship between comments
Cyberbullying is a underlying problem in social networking service, threatening users' mental and physical health. Previous research on automated cyberbullying detection is mostly textual or social based methods. Cyberbullying content is identified through a set of textual features within the content in the former method and through social information surrounding the content in the latter method. Those methods can not cater different cyberbullying standard for individual SNS user since each content is evaluated using same features. Therefore, in this article we propose a automated cyberbullying detection method that utilises the parent-child relationship between comments to capture the reaction from a third party to detect cyberbullying comments. We were able to improve the effectiveness of cyberbullying detection using only publicly available data.
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