Open AccessHate Speech Detection using ML Algorithm
Author(s) -
Prof. Deepali N. Bhaturkar,
Sukhada Joshi,
Snehal Shekar Shinde,
Purva Kulkarni,
Vaishnavi Desai
Publication year - 2022
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-3207
Subject(s) - witness , social media , creed , computer science , statement (logic) , support vector machine , the internet , nationality , caste , artificial intelligence , internet privacy , speech recognition , psychology , world wide web , political science , immigration , law , programming language
The difficulties that must be overcome when dealing with hate speech are not new. Hateful acts on social media have increased dramatically in recent years as a result of increased internet usage. Thanks to advancements in technology, it is now possible to provide a platform where people may freely express their thoughts and experiences. If this is the case, it will not be a problem. However, we sometimes witness hostile comments circulating on social media that are directed at a specific person or group. Hate speech is a statement that discriminates against a person or a group of people based on caste, creed, nationality, or other factors. Our study tries to address the aforementioned issue by utilising Deep Learning techniques to recognise hate speech and categorise it into several categories such as extremely positive, negative, or neutral. For classification, the SVM method was utilised.