Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang

Daphna Keidar, Andreas Opedal, Zhijing Jin, Mrinmaya Sachan


Abstract
Languages are continuously undergoing changes, and the mechanisms that underlie these changes are still a matter of debate. In this work, we approach language evolution through the lens of causality in order to model not only how various distributional factors associate with language change, but how they causally affect it. In particular, we study slang, which is an informal language that is typically restricted to a specific group or social setting. We analyze the semantic change and frequency shift of slang words and compare them to those of standard, nonslang words. With causal discovery and causal inference techniques, we measure the effect that word type (slang/nonslang) has on both semantic change and frequency shift, as well as its relationship to frequency, polysemy and part of speech. Our analysis provides some new insights in the study of language change, e.g., we show that slang words undergo less semantic change but tend to have larger frequency shifts over time.
Anthology ID:
2022.acl-long.101
Volume:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
May
Year:
2022
Address:
Dublin, Ireland
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1422–1442
Language:
URL:
https://aclanthology.org/2022.acl-long.101
DOI:
10.18653/v1/2022.acl-long.101
Bibkey:
Cite (ACL):
Daphna Keidar, Andreas Opedal, Zhijing Jin, and Mrinmaya Sachan. 2022. Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1422–1442, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang (Keidar et al., ACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.acl-long.101.pdf
Software:
 2022.acl-long.101.software.zip
Code
 andreasopedal/slangvolution