Open AccessAutomatic Hate Speech Detection: A Literature Review
Author(s) -
Mohiyaddeen,
Shifaulla Siddiqui
Publication year - 2021
Publication title -
international journal of engineering and management research
Language(s) - English
Resource type - Journals
eISSN - 2394-6962
pISSN - 2250-0758
DOI - 10.31033/ijemr.11.2.17
Subject(s) - offensive , voice activity detection , computer science , social media , the internet , speech recognition , emotion detection , artificial intelligence , speech processing , world wide web , engineering , emotion recognition , operations research
Hate speech has been an ongoing problem on the Internet for many years. Besides, social media, especially Facebook, and Twitter have given it a global stage where those hate speeches can spread far more rapidly. Every social media platform needs to implement an effective hate speech detection system to remove offensive content in real-time. There are various approaches to identify hate speech, such as Rule-Based, Machine Learning based, deep learning based and Hybrid approach. Since this is a review paper, we explained the valuable works of various authors who have invested their valuable time in studying to identifying hate speech using various approaches.