• Satrughan kumar
• Arun kumar
• Sandeep kumar

The increasing prevalence of social media and information sharing has undoubtedly benefited society in numerous ways. However, it has also brought about significant challenges, particularly concerning the proliferation of hate speech messages. To address this pressing issue within the realm of social media, recent studies have harnessed various feature engineering techniques and machine learning algorithms to automatically identify and combat hate speech across different datasets. To date, there has been no comprehensive study that systematically compares the myriad feature engineering techniques and machine learning algorithms, aiming to determine which combinations yield superior results on a commonly accessible dataset. As a response to this research gap, our paper sets out to conduct such a comparative analysis. We seek to assess the performance of three distinct feature engineering techniques in conjunction with eight diverse machine learning algorithms. Our experimental findings demonstrate that when employing bigram features in combination with the support vector machine (SVM) algorithm, the highest overall accuracy, reaching 89%, is achieved. This outcome suggests that this specific approach holds significant promise in the battle against hate speech The implications of our study extend beyond the research community. It holds practical significance by providing a foundational understanding of hate speech detection and can serve as a benchmark for future investigations in this domain. Furthermore, the insights derived from these comparative analyses will serve as state-of-the-art techniques for assessing and guiding future research endeavours focused on automated text classification techniques.

Convolutional Neural Network, Decision Tree, Natural Language Processing

"Hate Speech Detection using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.j490-j499, March-2024, Available :http://www.jetir.org/papers/JETIR2403966.pdf

"Hate Speech Detection using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppj490-j499, March-2024, Available at : http://www.jetir.org/papers/JETIR2403966.pdf