A Review on Emotion Based Harmful Speech Detection Using Machine Learning

The paper represents the state-of-the-art review of the machine learning methods for hate speech detection. This paper reviews novel applications of machine learning algorithms in hate speech. The machine learning based three algorithms i.e., Long-Short Term Memory, random forest, convolution neural network found to be most useful in hate speech detection. These algorithms are found to be most useful for twitter, Facebook, and other social platforms. This paper briefly surveys the most usable deep learning algorithms for detecting the hate speech in Arabic, English, Hindi, and other languages. The review result shows that the mentioned machine learning algorithms give an excellent results over other deep learning algorithm. Therefore, these three algorithms are widely acceptable for the evaluation of hate speech.