Using Deep Learning to Detect Islamophobia on Reddit

Esraa Aldreabi, Justin Lee, Jeremy Blackburn
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引用次数: 3

Abstract

Islamophobia, a negative predilection towards the Muslim community, is present on social media platforms. In addition to causing harm to victims, it also hurts the reputation of social media platforms that claim to provide a safe online environment for all users. The volume of social media content is impossible to be manually reviewed, thus, it is important to find automated solutions to combat hate speech on social media platforms. Machine learning approaches have been used in the literature as a way to automate hate speech detection. In this paper, we use deep learning techniques to detect Islamophobia over Reddit and topic modeling to analyze the content and reveal topics from comments identified as Islamophobic. Some topics we identified include the Islamic dress code, religious practices, marriage, and politics. To detect Islamophobia, we used deep learning models. The highest performance was achieved with BERTbase+CNN, with an F1-Score of 0.92.
使用深度学习检测Reddit上的伊斯兰恐惧症
“伊斯兰恐惧症”是一种对穆斯林社区的负面偏好,在社交媒体平台上随处可见。除了对受害者造成伤害外,它还损害了声称为所有用户提供安全在线环境的社交媒体平台的声誉。社交媒体内容的数量是不可能被人工审查的,因此,找到自动解决方案来打击社交媒体平台上的仇恨言论是很重要的。在文献中,机器学习方法被用作自动检测仇恨言论的方法。在本文中,我们使用深度学习技术来检测Reddit上的伊斯兰恐惧症,并使用主题建模来分析内容并从被确定为伊斯兰恐惧症的评论中揭示主题。我们确定的一些主题包括伊斯兰教的着装规范、宗教习俗、婚姻和政治。为了检测伊斯兰恐惧症,我们使用了深度学习模型。BERTbase+CNN表现最好,F1-Score为0.92。
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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