Emoji powered capsule network to detect type and target of offensive posts in social media

Abstract

This paper describes a novel research approach to detect type and target of offensive posts in social media using a capsule network. The input to the network was character embeddings combined with emoji embeddings. The approach was evaluated on all the subtasks in SemEval-2019 Task 6: OffensEval: Identifying and Categorizing Offensive Language in Social Media. The evaluation also showed that even though the capsule networks have not been used commonly in NLP tasks, they can outperform existing state of the art solutions for offensive language detection in social media.