Emoji Powered Capsule Network to Detect Type and Target of Offensive Posts in Social Media

Tharindu Ranasinghe, Hansi Hettiarachchi

    Research output: Chapter in Book/Published conference outputConference publication


    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 three subtasks in Task 6 - SemEval 2019: 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 natural language processing tasks, they can outperform existing state of the art solutions for offensive language detection in social media.
    Original languageEnglish
    Title of host publicationInternational Conference on Recent Advances in Natural Language Processing (RANLP 2019)
    Number of pages7
    Publication statusPublished - Sept 2019

    Bibliographical note

    ACL materials are Copyright © 1963–2023 ACL. Materials published in or after 2016 are licensed on a Creative Commons Attribution 4.0 International License.

    Cite this