Our study explores offensive and hate speech detection for the Arabic language, as previous studies are minimal.

Steven Zimmerman, Udo Kruschwitz, and Chris Fox. 2018. Improving Hate Speech Detection with Deep Learning Ensembles. In Proceedings of the Eleventh ...

This paper develops a semi-supervised learning approach with self-training to benefit from the abundant amount of social media content and develop a robust hate ...

Our ensemble models achieve an 83% hate recall on the HON dataset, surpassing the performance of the state of the art deep models. We demonstrate that weak ...

This study proposes a novel approach that leverages ensemble learning and semi-supervised learning based on previously manually labeled language models to ...

Experimental results for a deep learning ensemble method that improves F-measure 2% over non- ensemble approaches and a nearly 5% increase over hand crafted ...

Dec 7, 2023 · We present here a large-scale empirical comparison of deep and shallow hate-speech detection methods, mediated through the three most commonly used datasets.

To address this issue, we leverage deep ensemble learning techniques to classify and automatically neutralize hate speech. By leveraging the. Hugging Face ...

Our study explores offensive and hate speech detection for the Arabic language, as previous studies are minimal.

This paper addresses the important problem of discerning hateful content in social media. We propose a detection scheme that is an ensemble of Recurrent Neural ...