WU_TLAXE at WASSA 2024 Explainability for Cross-Lingual Emotion in Tweets Shared Task 1: Emotion through Translation using TwHIN-BERT and GPT

Jon Davenport, Keren Ruditsky, Anna Batra, Yulha Lhawa, Gina-Anne Levow


Abstract
This paper describes our task 1 submission for the WASSA 2024 shared task on Explainability for Cross-lingual Emotion in Tweets. Our task is to predict the correct emotion label (Anger, Sadness, Fear, Joy, Love, and Neutral) for a dataset of English, Dutch, French, Spanish, and Russian tweets, while training exclusively on English emotion labeled data, to reveal what kind of emotion detection information is transferable cross-language (Maladry et al., 2024). To that end, we used an ensemble of models with a GPT-4 decider. Our ensemble consisted of a few-shot GPT-4 prompt system and a TwHIN-BERT system fine-tuned on the EXALT and additional English data. We ranked 8th place under the name WU_TLAXE with an F1 Macro score of 0.573 on the test set. We also experimented with an English-only TwHIN-BERT model by translating the other languages into English for inference, which proved to be worse than the other models.
Anthology ID:
2024.wassa-1.52
Volume:
Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Orphée De Clercq, Valentin Barriere, Jeremy Barnes, Roman Klinger, João Sedoc, Shabnam Tafreshi
Venues:
WASSA | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
523–527
Language:
URL:
https://aclanthology.org/2024.wassa-1.52
DOI:
10.18653/v1/2024.wassa-1.52
Bibkey:
Cite (ACL):
Jon Davenport, Keren Ruditsky, Anna Batra, Yulha Lhawa, and Gina-Anne Levow. 2024. WU_TLAXE at WASSA 2024 Explainability for Cross-Lingual Emotion in Tweets Shared Task 1: Emotion through Translation using TwHIN-BERT and GPT. In Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, pages 523–527, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
WU_TLAXE at WASSA 2024 Explainability for Cross-Lingual Emotion in Tweets Shared Task 1: Emotion through Translation using TwHIN-BERT and GPT (Davenport et al., WASSA-WS 2024)
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PDF:
https://preview.aclanthology.org/autopr/2024.wassa-1.52.pdf