Hate Speech Detection Using Decision Tree Algorithm
J. Lavanya
Department of IT, Sreenidhi Institute of Science and Technology (Autonomous), Hyderabad, India.
M. Ramesh
Department of IT, Sreenidhi Institute of Science and Technology (Autonomous), Hyderabad, India.
J. Sravan Kumar
Department of IT, Sreenidhi Institute of Science and Technology (Autonomous), Hyderabad, India.
G. Rajaramesh *
Department of IT, Sreenidhi Institute of Science and Technology (Autonomous), Hyderabad, India.
Subhani Shaik
Department of IT, Sreenidhi Institute of Science and Technology (Autonomous), Hyderabad, India.
*Author to whom correspondence should be addressed.
Abstract
The advancement of the internet and social media, people has access to various platforms to freely share their thoughts and opinions on various topics. However, this freedom of expression is abused to incite hatred against individuals or groups of people based on race, religion, gender, etc. question. Therefore, to address this emerging problem on social media sites, recent studies have used various feature engineering techniques and machine learning algorithms to automatically detect hate speech posts on different datasets. Advances in machine learning have intrigued researchers seeking and implementing solutions to the problem of hate speech. Currently, we are using decision tree algorithm technique to detect hate speech using text data.
Keywords: Groups of people, social media, feature engineering, decision tree