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The Effect of Round-Trip Translation on Fairness in Sentiment Analysis. / Christiansen, Jonathan Gabel ; Gammelgaard, Mathias Lykke ; Søgaard, Anders.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2021. s. 4423–4428.
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
Christiansen, JG, Gammelgaard, ML
& Søgaard, A 2021,
The Effect of Round-Trip Translation on Fairness in Sentiment Analysis. i
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, s. 4423–4428, 2021 Conference on Empirical Methods in Natural Language Processing,
07/11/2021.
https://doi.org/10.18653/v1/2021.emnlp-main.363APA
Christiansen, J. G., Gammelgaard, M. L.
, & Søgaard, A. (2021).
The Effect of Round-Trip Translation on Fairness in Sentiment Analysis. I
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (s. 4423–4428). Association for Computational Linguistics.
https://doi.org/10.18653/v1/2021.emnlp-main.363Vancouver
Christiansen JG, Gammelgaard ML
, Søgaard A.
The Effect of Round-Trip Translation on Fairness in Sentiment Analysis. I Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. 2021. s. 4423–4428
https://doi.org/10.18653/v1/2021.emnlp-main.363Author
Christiansen, Jonathan Gabel ; Gammelgaard, Mathias Lykke ; Søgaard, Anders. / The Effect of Round-Trip Translation on Fairness in Sentiment Analysis. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2021. s. 4423–4428
Bibtex
@inproceedings{d972adf18c864d178fbfa411720181f5,
title = "The Effect of Round-Trip Translation on Fairness in Sentiment Analysis",
abstract = "Sentiment analysis systems have been shown to exhibit sensitivity to protected attributes. Round-trip translation, on the other hand, has been shown to normalize text. We explore the impact of round-trip translation on the demographic parity of sentiment classifiers and show how round-trip translation consistently improves classification fairness at test time (reducing up to 47% of between-group gaps). We also explore the idea of retraining sentiment classifiers on round-trip-translated data.",
author = "Christiansen, {Jonathan Gabel} and Gammelgaard, {Mathias Lykke} and Anders S{\o}gaard",
year = "2021",
doi = "10.18653/v1/2021.emnlp-main.363",
language = "English",
pages = "4423–4428",
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
publisher = "Association for Computational Linguistics",
note = "2021 Conference on Empirical Methods in Natural Language Processing ; Conference date: 07-11-2021 Through 11-11-2021",
}
RIS
TY - GEN
T1 - The Effect of Round-Trip Translation on Fairness in Sentiment Analysis
AU - Christiansen, Jonathan Gabel
AU - Gammelgaard, Mathias Lykke
AU - Søgaard, Anders
PY - 2021
Y1 - 2021
N2 - Sentiment analysis systems have been shown to exhibit sensitivity to protected attributes. Round-trip translation, on the other hand, has been shown to normalize text. We explore the impact of round-trip translation on the demographic parity of sentiment classifiers and show how round-trip translation consistently improves classification fairness at test time (reducing up to 47% of between-group gaps). We also explore the idea of retraining sentiment classifiers on round-trip-translated data.
AB - Sentiment analysis systems have been shown to exhibit sensitivity to protected attributes. Round-trip translation, on the other hand, has been shown to normalize text. We explore the impact of round-trip translation on the demographic parity of sentiment classifiers and show how round-trip translation consistently improves classification fairness at test time (reducing up to 47% of between-group gaps). We also explore the idea of retraining sentiment classifiers on round-trip-translated data.
U2 - 10.18653/v1/2021.emnlp-main.363
DO - 10.18653/v1/2021.emnlp-main.363
M3 - Article in proceedings
SP - 4423
EP - 4428
BT - Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
PB - Association for Computational Linguistics
T2 - 2021 Conference on Empirical Methods in Natural Language Processing
Y2 - 7 November 2021 through 11 November 2021
ER -
