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Title |
Social Media and Online Islamophobia: A Hate Behavior Detection Model |
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Author |
Abdulwahab Ali Almazroi, Asad Ali Shah, and Fathey Mohammed |
| Citation |
Vol. 25 No. 3 pp. 75-80 |
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Abstract |
Muslim community has faced a lot of hatred towards them due to the rise in Islamophobia. Taking no measures to control Islamophobia can create fear among the Muslim community while at the same time giving others an open hand to spread hate and toxic remarks toward Muslims. While Muslim leaders and countries are taking measures to stop Islamophobia through awareness and building content to share Islam’s true peaceful and moderate image, it does not help in controlling the spread of Islamophobia on social media platforms. In this regard, this research proposes a framework capable of detecting Islamophobic content. The proposed solution achieves this using natural language and artificial intelligence techniques such as keyword detection, tone analyzer, machine learning, impartiality ratio, and more. The proposed model is also capable of categorizing comments based on their severity and context. The research is hopeful that the proposed framework would allow experts to detect such posts causing Islamophobia early and report them so they can be taken down timely before being widespread. The successful completion of this research will not only have positive implications for the Muslim community but will also allow experts and researchers from other areas to use the same model in combating hateful and toxic speech on other platforms. |
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Keywords |
Social Media; Detection; Islamophobia; Hate |
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