Tracing Semantic Variation in Slang

Zhewei Sun, Yang Xu


Abstract
The meaning of a slang term can vary in different communities. However, slang semantic variation is not well understood and under-explored in the natural language processing of slang. One existing view argues that slang semantic variation is driven by culture-dependent communicative needs. An alternative view focuses on slang’s social functions suggesting that the desire to foster semantic distinction may have led to the historical emergence of community-specific slang senses. We explore these theories using computational models and test them against historical slang dictionary entries, with a focus on characterizing regularity in the geographical variation of slang usages attested in the US and the UK over the past two centuries. We show that our models are able to predict the regional identity of emerging slang word meanings from historical slang records. We offer empirical evidence that both communicative need and semantic distinction play a role in the variation of slang meaning yet their relative importance fluctuates over the course of history. Our work offers an opportunity for incorporating historical cultural elements into the natural language processing of slang.
Anthology ID:
2022.emnlp-main.84
Volume:
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Editors:
Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1299–1313
Language:
URL:
https://aclanthology.org/2022.emnlp-main.84
DOI:
10.18653/v1/2022.emnlp-main.84
Bibkey:
Cite (ACL):
Zhewei Sun and Yang Xu. 2022. Tracing Semantic Variation in Slang. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 1299–1313, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
Tracing Semantic Variation in Slang (Sun & Xu, EMNLP 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.emnlp-main.84.pdf