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How language-dependent is emotion detection? Evidence from multilingual BERT

Luna De Bruyne (UGent) , Pranaydeep Singh (UGent) , Orphée De Clercq (UGent) , Els Lefever (UGent) and Veronique Hoste (UGent)
(2022) Proceedings of the 2nd Workshop on Multi-lingual Representation Learning (MRL). p.76-85
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Abstract
As emotion analysis in text has gained a lot of attention in the field of natural language processing, differences in emotion expression across languages could have consequences for how emotion detection models work. We evaluate the language-dependence of an mBERT-based emotion detection model by comparing language identification performance before and after fine-tuning on emotion detection, and performing (adjusted) zero-shot experiments to assess whether emotion detection models rely on language-specific information. When dealing with typologically dissimilar languages, we found evidence for the language-dependence of emotion detection.

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MLA
De Bruyne, Luna, et al. “How Language-Dependent Is Emotion Detection? Evidence from Multilingual BERT.” Proceedings of the 2nd Workshop on Multi-Lingual Representation Learning (MRL), Association for Computational Linguistics, 2022, pp. 76–85.
APA
De Bruyne, L., Singh, P., De Clercq, O., Lefever, E., & Hoste, V. (2022). How language-dependent is emotion detection? Evidence from multilingual BERT. Proceedings of the 2nd Workshop on Multi-Lingual Representation Learning (MRL), 76–85. Association for Computational Linguistics.
Chicago author-date
De Bruyne, Luna, Pranaydeep Singh, Orphée De Clercq, Els Lefever, and Veronique Hoste. 2022. “How Language-Dependent Is Emotion Detection? Evidence from Multilingual BERT.” In Proceedings of the 2nd Workshop on Multi-Lingual Representation Learning (MRL), 76–85. Association for Computational Linguistics.
Chicago author-date (all authors)
De Bruyne, Luna, Pranaydeep Singh, Orphée De Clercq, Els Lefever, and Veronique Hoste. 2022. “How Language-Dependent Is Emotion Detection? Evidence from Multilingual BERT.” In Proceedings of the 2nd Workshop on Multi-Lingual Representation Learning (MRL), 76–85. Association for Computational Linguistics.
Vancouver
1.
De Bruyne L, Singh P, De Clercq O, Lefever E, Hoste V. How language-dependent is emotion detection? Evidence from multilingual BERT. In: Proceedings of the 2nd Workshop on Multi-lingual Representation Learning (MRL). Association for Computational Linguistics; 2022. p. 76–85.
IEEE
[1]
L. De Bruyne, P. Singh, O. De Clercq, E. Lefever, and V. Hoste, “How language-dependent is emotion detection? Evidence from multilingual BERT,” in Proceedings of the 2nd Workshop on Multi-lingual Representation Learning (MRL), Abu Dhabi, United Arab Emirates (Hybrid), 2022, pp. 76–85.
@inproceedings{01GPDJHVE9ESH8GJ8ABEA50S2J,
  abstract     = {{As emotion analysis in text has gained a lot of attention in the field of natural language processing, differences in emotion expression across languages could have consequences for how emotion detection models work. We evaluate the language-dependence of an mBERT-based emotion detection model by comparing language identification performance before and after fine-tuning on emotion detection, and performing (adjusted) zero-shot experiments to assess whether emotion detection models rely on language-specific information. When dealing with typologically dissimilar languages, we found evidence for the language-dependence of emotion detection.}},
  author       = {{De Bruyne, Luna and Singh, Pranaydeep and De Clercq, Orphée and Lefever, Els and Hoste, Veronique}},
  booktitle    = {{Proceedings of the 2nd Workshop on Multi-lingual Representation Learning (MRL)}},
  isbn         = {{9781959429166}},
  language     = {{eng}},
  location     = {{Abu Dhabi, United Arab Emirates (Hybrid)}},
  pages        = {{76--85}},
  publisher    = {{Association for Computational Linguistics}},
  title        = {{How language-dependent is emotion detection? Evidence from multilingual BERT}},
  url          = {{https://aclanthology.org/2022.mrl-1.0}},
  year         = {{2022}},
}