Hate Speech Detection in Social Networks using Machine Learning and Deep Learning Methods

Hate speech on social media platforms like Twitter is a growing concern that poses challenges to maintaining a healthy online environment and fostering constructive communication. Effective detection and monitoring of hate speech are crucial for mitigating its adverse impact on individuals and communities. In this paper, we propose a comprehensive approach for hate speech detection on Twitter using both traditional machine learning and deep learning techniques. Our research encompasses a thorough comparison of these techniques to determine their effectiveness in identifying hate speech on Twitter.

Hate Speech Detection in Social Networks using Machine Learning and Deep Learning Methods / A.Toktarova, D.Syrlybay, B. Myrzakhmetova, G. Anuarbekova, G. Rakhimbayeva, B. Zhylanbaeva, N. Suieuova, M. Kerimbekov // International Journal of Advanced Computer Science and Applications (IJACSA). – 2023. – № 5.

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