Patro, J. (2020). Code-Switching Patterns Can Be an Effective Route to Improve Performance of Downstream NLP Applications: A Case Study of Humour, Sarcasm and Hate Speech Detection. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5-10, 2020 (pp. 1018-1023). (Proceedings of the Annual Meeting of the Association for Computational Linguistics). https://doi.org/10.18653/v1/2020.acl-main.96

@inproceedings{ce78b8b5bb3a4944a00f86d34ec3c5f4,
title = "Code-Switching Patterns Can Be an Effective Route to Improve Performance of Downstream NLP Applications: A Case Study of Humour, Sarcasm and Hate Speech Detection",
abstract = "In this paper we demonstrate how code-switching patterns can be utilised to improve various downstream NLP applications. In particular, we encode different switching features to improve humour, sarcasm and hate speech detection tasks. We believe that this simple linguistic observation can also be potentially helpful in improving other similar NLP applications.",
author = "Jasabanta Patro",
note = "Publisher Copyright: {\textcopyright} 2020 Association for Computational Linguistics Copyright: Copyright 2023 Elsevier B.V., All rights reserved.",
year = "2020",
doi = "10.18653/v1/2020.acl-main.96",
language = "English",
series = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",
pages = "1018--1023",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5-10, 2020",
}