Detection of hate speech in Social media memes: A comparative Analysis

Abstract

This work projects light upon the challenges of hate speech detection in memes and demonstrates the various machine learning model to automatically detect hate in the internet memes. Memes are the visual content shared on the social media in the form of combination of picture and some textual phrases to depict light humour or jokes. However, some images in the form of memes can also be used to convey misinformation and hate, so their early automatic detection is necessary to stop the hate spreading to wide range of users or population which may cause unrest and harm to human life and property. In this paper, the hateful meme dataset by Facebook AI has been used to test the various unimodal and a multimodal approach to baseline performance for these models and highlight the challenges these hate memes pose to the community.