Hate Speech Detection on Social Media Using Machine Learning

Algorithms

Rupesh Chaudhari, Ritik Gade, Pranav Gawali, Mangesh Gite, Dr. A. B. Pawar

Computer Engineering, Sanjivani College of Engineering, Kopargoan, Savitribai Phule Pune University, India.

rupeshchaudhari2151@gmail.com, ritikgade22@gmail.com, pranavgawali2510@gmail.com,

mangeshgite9@gmail.com, pawaranilcomp@sanjivani.org.in

Abstract

There is an enormous growth of social media which fully promotes freedom of expression through its

anonymity feature. Freedom of expression is a human right but hate speech towards a person or group

based on race, caste, religion, ethnic or national origin, sex, disability, gender identity, etc. is an abuse of

this sovereignty. It seriously promotes violence or hate crimes and creates an imbalance in society by

damaging peace, credibility, and human rights, etc. To overcome this problem, the hate speech detection

model is made which will classify the speech and if the speech used by user is containing hate word, it

will be detected and system will sent an alert message to user about it. In order to solve various hate

speech problems we use some of the machine learning algorithms such as logistic regression and random

forest. If user disrupts cyber guidelines, then strict action shall be taken and user’s account will be ban

forever. This help to reduce cyber crimes in effective and efficient manner.

Keywords: Machine learning, Hate speech, Natural language processing, Data pre-processing, Random forest,

Logistic regression, Hate word classification.