Arabic Cyberbullying Detection: Using Deep Learning

Batoul Haidar, M. Chamoun, A. Serhrouchni
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引用次数: 23

Abstract

As much as internet and smart devices are taking a big role in the lives of children and adolescents, also the threat of Cyberbullying on the lives and wellbeing of those youngsters is rising. The threat of cyberbullying is acknowledged around the world enerally and in the Arabic areas specifically. A lot of research is done for finding automated solutions for cyberbullying detection in several languages, but not much has been done for Arabic Language. At the other hand, a lot of interest is invested in Deep Learning techniques, where Deep Learning has been applied in several areas and showed vast success. Thus this paper proposes a solution that employs Deep Learning methods in the process of Arabic Cyberbullying Detection. Specifically a Feed Forward Neural Network is trained on an Arabic Dataset for the purpose of cyberbullying detection.
阿拉伯网络欺凌检测:使用深度学习
尽管互联网和智能设备在儿童和青少年的生活中发挥着重要作用,但网络欺凌对这些青少年的生活和福祉的威胁也在上升。网络欺凌的威胁在世界各地普遍得到承认,特别是在阿拉伯地区。很多研究都是为了寻找几种语言的网络欺凌检测自动化解决方案,但针对阿拉伯语的研究却不多。另一方面,人们对深度学习技术很感兴趣,深度学习已经在几个领域得到了应用,并取得了巨大的成功。因此,本文提出了一种在阿拉伯网络欺凌检测过程中使用深度学习方法的解决方案。具体来说,前馈神经网络在阿拉伯数据集上进行训练,用于网络欺凌检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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