文章基本信息

标题：Detection of Hate Speech in Social Networks: A Survey on Multilingual Corpus
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作者：Areej Al-Hassan ; Hmood Al-Dossari
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2019
卷号：9
期号：2
页码：83-100
DOI：10.5121/csit.2019.90208
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：In social media platforms, hate speech can be a reason of “cyber conflict” which can affect social life in both of individual-level and country-level. Hateful and antagonistic content propagated via social networks has the potential to cause harm and suffering on an individual basis and lead to social tension and disorder beyond cyber space. However, social networks cannot control all the content that users post. For this reason, there is a demand for automatic detection of hate speech. This demand particularly raises when the content is written in complex languages (e.g. Arabic). Arabic text is known with its challenges, complexity and scarcity of its resources. This paper will present a background on hate speech and its related detection approaches. In addition, the recent contributions on hate speech and its related anti-social behaviour topics will be reviewed. Finally, challenges and recommendations for the Arabic hate speech detection problem will be presented.
关键词：Text Mining; Social Networks; Hate Speech; Natural Language Processing; Arabic NLP