A Review on Hate Speech on Social Media, Impact on Society and Counter Measures

Social media has emerged as a powerful communication platform worldwide. The unprecedented growth of digital information has led to many crucial and challenging issues. Numerous technologies have provided a platform to the users to interact people from various countries, cultures and ethnicities. Although these platforms provide an opportunity to connect anywhere worldwide and the constructive growth of this inclusive communication are noticeable. Due to the nature of invisibility, mystery, and accessibility of such web applications, users can mask their identities and engage in xenophobic, racist, and sexist discourses with ease and impunity. This is known as dis-inhibition effect in social media in which social users are not capable to communicate face-to-face. This paper presents a review on machine learning and deep learning based approaches for identifying hate speech on social media.