LITHUANIAN HATE SPEECH CLASSIFICATION USING DEEP LEARNING METHODS

Abstract

The ever-increasing amount of online content and the opportunity for everyone to express their opinions online leads to frequent encounters with social problems: bullying, insults, and hate speech. Some online portals are taking steps to stop this, such as no longer allowing user-generated comments to be made anonymously, removing the possibility to comment under the articles, and some portals employ moderators who identify and eliminate hate speech. However, given the large number of comments, an appropriately large number of people are required to do this work. The rapid development of artificial intelligence in the language technology area may be the solution to this problem. Automated hate speech detection would allow to manage the ever-increasing amount of online content, therefore we report hate speech classification for Lithuanian language by application of deep learning.