Hate Speech Detection Using Natural Language Processing: Applications and Challenges
Anil Singh Parihar, Surendrabikram Thapa, Sushruti Mishra
Abstract
The internet has become a common platform for everyone to share their ideas and opinions. The user has freedom to post whatever he/she likes in social networking and blogging sites. However, sometimes the content when directed towards certain group of individuals with an intention to incite hate or discrimination, causes a turmoil in the society. Such content is known as hate speech. Hate speech can be a serious problem to peace and harmony in the society. There are instances where hate speech have led to social unrest and extremism. Thus, hate speech in the internet needs to be monitored. In this paper, we discuss the relevant works done in the field of hate speech detection. Different types of hate speech like racism, sexism, religious hate speech, etc. and the various methods proposed to tackle them are discussed. Further, we identify the challenges and propose the solutions to challenges in hate speech detection in the public internet sphere.