A Collaborative Learning Approach for Identifying Hateful Speech on Social Media Applications

Social media, hailed for connecting people across the globe, has become an integral part of our daily lives. However, the same platforms designed to foster communication and community have become breeding grounds for hateful content. Hate speech, discrimination, and online harassment are pervasive issues that threaten the fabric of digital society. . Machine learning models are indispensable from identification of radical content due to the sheer size and complexity of the data. In this approach, a collaborative learning based approach has been proposed for identifying hateful content. It has been shown that the proposed approach attains higher classification accuracy compared to existing work in the domain.