Advanced Deep Learning Approaches for Hate Speech Detection

Abstract

At present, the influence of social networks on a global scale is increasing, the number of users is increasing significantly, and massive amounts of information are being created every day. How to automatically and efficiently identify harmful information, especially hate speech, has become an important issue in the governance of the network environment. In order to improve the screening efficiency of information containing hate speech, deep learning is applied in this field. Although the research work around this task has made great progress, there are very few reviews on this task, lack of a comprehensive review of the latest development in recent years and can not provide help for researchers who are interested in this task. Therefore, we give an overview of the deep learning applied in hate speech, introducing new ideas for solving this task in recent years, and propose potential problems in the task and analyze it.