Impoverished Language Technology: The Lack of (Social) Class in NLP

Amanda Cercas Curry, Zeerak Talat, Dirk Hovy


Abstract
Since Labov’s foundational 1964 work on the social stratification of language, linguistics has dedicated concerted efforts towards understanding the relationships between socio-demographic factors and language production and perception. Despite the large body of evidence identifying significant relationships between socio-demographic factors and language production, relatively few of these factors have been investigated in the context of NLP technology. While age and gender are well covered, Labov’s initial target, socio-economic class, is largely absent. We survey the existing Natural Language Processing (NLP) literature and find that only 20 papers even mention socio-economic status. However, the majority of those papers do not engage with class beyond collecting information of annotator-demographics. Given this research lacuna, we provide a definition of class that can be operationalised by NLP researchers, and argue for including socio-economic class in future language technologies.
Anthology ID:
2024.lrec-main.761
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
8675–8682
Language:
URL:
https://aclanthology.org/2024.lrec-main.761
DOI:
Bibkey:
Cite (ACL):
Amanda Cercas Curry, Zeerak Talat, and Dirk Hovy. 2024. Impoverished Language Technology: The Lack of (Social) Class in NLP. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 8675–8682, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Impoverished Language Technology: The Lack of (Social) Class in NLP (Cercas Curry et al., LREC-COLING 2024)
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PDF:
https://aclanthology.org/2024.lrec-main.761.pdf