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    <abstract>Emotion classification on code-mixed texts has been widely used in real-world applications. In this paper, we build a system that participates in the WASSA 2023 Shared Task 2 for emotion classification on code-mixed text messages from Roman Urdu and English. The main goal of the proposed method is to adopt a text-mixed data augmentation for robust code-mixed text representation. We mix texts with both multi-label (track 1) and multi-class (track 2) annotations in a unified multilingual pre-trained model, i.e., XLM-RoBERTa, for both subtasks. Our results show that the proposed text-mixed method performs competitively, ranking first in both tracks, achieving an average Macro F1 score of 0.9782 on the multi-label track and of 0.9329 on the multi-class track.</abstract>
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%0 Conference Proceedings
%T YNU-HPCC at WASSA 2023: Using Text-Mixed Data Augmentation for Emotion Classification on Code-Mixed Text Message
%A Ran, Xuqiao
%A Zhang, You
%A Wang, Jin
%A Xu, Dan
%A Zhang, Xuejie
%Y Barnes, Jeremy
%Y De Clercq, Orphée
%Y Klinger, Roman
%S Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F ran-etal-2023-ynu
%X Emotion classification on code-mixed texts has been widely used in real-world applications. In this paper, we build a system that participates in the WASSA 2023 Shared Task 2 for emotion classification on code-mixed text messages from Roman Urdu and English. The main goal of the proposed method is to adopt a text-mixed data augmentation for robust code-mixed text representation. We mix texts with both multi-label (track 1) and multi-class (track 2) annotations in a unified multilingual pre-trained model, i.e., XLM-RoBERTa, for both subtasks. Our results show that the proposed text-mixed method performs competitively, ranking first in both tracks, achieving an average Macro F1 score of 0.9782 on the multi-label track and of 0.9329 on the multi-class track.
%R 10.18653/v1/2023.wassa-1.60
%U https://aclanthology.org/2023.wassa-1.60
%U https://doi.org/10.18653/v1/2023.wassa-1.60
%P 611-615

Markdown (Informal)

[YNU-HPCC at WASSA 2023: Using Text-Mixed Data Augmentation for Emotion Classification on Code-Mixed Text Message](https://aclanthology.org/2023.wassa-1.60) (Ran et al., WASSA 2023)

• YNU-HPCC at WASSA 2023: Using Text-Mixed Data Augmentation for Emotion Classification on Code-Mixed Text Message (Ran et al., WASSA 2023)

ACL

• Xuqiao Ran, You Zhang, Jin Wang, Dan Xu, and Xuejie Zhang. 2023. YNU-HPCC at WASSA 2023: Using Text-Mixed Data Augmentation for Emotion Classification on Code-Mixed Text Message. In Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, pages 611–615, Toronto, Canada. Association for Computational Linguistics.