Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabic

António Câmara, Nina Taneja, Tamjeed Azad, Emily Allaway, Richard Zemel


Abstract
As natural language processing systems become more widespread, it is necessary to address fairness issues in their implementation and deployment to ensure that their negative impacts on society are understood and minimized. However, there is limited work that studies fairness using a multilingual and intersectional framework or on downstream tasks. In this paper, we introduce four multilingual Equity Evaluation Corpora, supplementary test sets designed to measure social biases, and a novel statistical framework for studying unisectional and intersectional social biases in natural language processing. We use these tools to measure gender, racial, ethnic, and intersectional social biases across five models trained on emotion regression tasks in English, Spanish, and Arabic. We find that many systems demonstrate statistically significant unisectional and intersectional social biases. We make our code and datasets available for download.
Anthology ID:
2022.ltedi-1.11
Volume:
Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion
Month:
May
Year:
2022
Address:
Dublin, Ireland
Editors:
Bharathi Raja Chakravarthi, B Bharathi, John P McCrae, Manel Zarrouk, Kalika Bali, Paul Buitelaar
Venue:
LTEDI
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
90–106
Language:
URL:
https://aclanthology.org/2022.ltedi-1.11
DOI:
10.18653/v1/2022.ltedi-1.11
Bibkey:
Cite (ACL):
António Câmara, Nina Taneja, Tamjeed Azad, Emily Allaway, and Richard Zemel. 2022. Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabic. In Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion, pages 90–106, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabic (Câmara et al., LTEDI 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.ltedi-1.11.pdf
Video:
 https://aclanthology.org/2022.ltedi-1.11.mp4