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 rising use of online amusement and information sharing has given critical promotion advantages to humankind. Regardless, this has in like manner prompted various troubles including the spreading likewise, sharing of scorn talk messages. Thus, to tackle this emerging issue in virtual diversion objections, continuous assessments utilized a combination of incorporated planning techniques and artificial intelligence estimations to distinguish the contempt talk messages on different datasets. Nevertheless, suppose, there is no audit to investigate the variety of component planning strategies and Artificial intelligence computations to evaluate which incorporate planning strategy and simulated intelligence estimation beat on a standard transparently open dataset. In the published paper we are going to distinguish discourse utilizing repetitive brain organization. In this system, we get the 87.38% accuracy for 300 epochs.

Keywords— Convolutional Neural Network, Deep Learning, Recurrent Neural Network