Poster
in
Affinity Workshop: Muslims in ML
Explainable Identification of Hate Speech towards Islam using Graph Neural Networks
Azmine Toushik Wasi
Keywords: [ Natural Language Processing ] [ Explainable AI ] [ graph neural networks ] [ Hate Speech Identification ] [ Hate Speech Detection ]
Islamophobic language is a prevalent challenge on online social interaction platforms. Identifying and eliminating such hatred is a crucial step towards a future of harmony and peace. This study presents a novel paradigm for identifying and explaining hate speech towards Islam using graph neural networks. Utilizing the intrinsic ability of graph neural networks to find, extract, and use relationships across disparate data points, our model consistently achieves outstanding performance while offering explanations for the underlying correlations and causation.