Deep Learning Based Hybrid Word Representation for Detection of Hate Speech
Aruna B. Bhat, Surabhi Adhikari, Khushi Kumari Jha, Hazrat Bilal Sadat · 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · 2022
In this era of very easy access to information, it has become very easier for anyone to share their ideas, opinions and beliefs. Internet being the most used space for all lets every user share their thoughts with just a click. With a lot of people sharing their ideas and opinions, it is obvious that there can be some dissatisfactions. Internet has witnessed some of the greatest social movements in the history. With smartphones available in every hand, people can join the movement easily and express their opinions. Social movements are drives related to a particular community which gets attention from the entire world. Social media mostly gets polarized into two parts, one in support of the movement and another in opposition of the movement. Machine learning algorithms give us the power to do the analysis of people's sentiment in the internet. Using the power of machine learning and its applications, this paper tries to do the fundamental analysis of which sides the twitter users are leaning to subsequently enable recognizing hate speech. With the help of tweets publicly available, the analysis is done using multiple deep learning algorithms.