AUTOMATED HATE SPEECH DETECTION USING RECURRENT NEURAL NETWORK

AUTOMATED HATE SPEECH DETECTION USING RECURRENT NEURAL NETWORK

Mr. Atharva Khurpe1, Mr. Aman Shaikh2, Mr. Swanand Muley3, Mr. Imaad Patel4, Prof. Rutika Shah5

1,2,3,4 UG Student, 5Asst. Professor, Dept. of Computer Engineering,

Trinity College of Engineering and Research, Pune, Maharashtra.

Abstract - The spread of online entertainment and information sharing has indeed brought significant advances to humanity. However, it has also created various challenges, such as the spread of derogatory content through means such as voicemail. Addressing this emerging problem requires continued consideration, especially in virtual environments, where innovative approaches combining design methods and artificial intelligence are used to identify and filter such content from various data sets. While efforts are being made to combat this problem, there is still a gap in design strategies for that purpose and a comprehensive overview of artificial intelligence algorithms. This includes the need for transparent evaluation criteria and publicly available datasets to benchmark performance and promote collaboration within the research community.

Keywords — Deep Learning, Recurrent Neural Network(RNN), Hate Speech Detection.