Automatic Hate Speech Detection: A Literature Review

Authors

  • Mohiyaddeen Student, Department of Computer Science, Integral University, INDIA
  • Dr. Shifaulla Siddiqui Professor, Department of Computer Science, Integral University, INDIA

DOI:

https://doi.org/10.31033/ijemr.11.2.16

Keywords:

Classification Algorithm, Machine Learning, Hate Speech, Deep Learning, Supervised Learning

Abstract

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.

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Published

2021-04-30

How to Cite

Mohiyaddeen, & Dr. Shifaulla Siddiqui. (2021). Automatic Hate Speech Detection: A Literature Review. International Journal of Engineering and Management Research, 11(2), 116–121. https://doi.org/10.31033/ijemr.11.2.16