Visualisation Methods for Diachronic Semantic Shift

Raef Kazi, Alessandra Amato, Shenghui Wang, Doina Bucur


Abstract
The meaning and usage of a concept or a word changes over time. These diachronic semantic shifts reflect the change of societal and cultural consensus as well as the evolution of science. The availability of large-scale corpora and recent success in language models have enabled researchers to analyse semantic shifts in great detail. However, current research lacks intuitive ways of presenting diachronic semantic shifts and making them comprehensive. In this paper, we study the PubMed dataset and compute semantic shifts across six decades. We develop three visualisation methods that can show, given a root word: the temporal change in its linguistic context, word re-occurrence, degree of similarity, time continuity, and separate trends per publisher location. We also propose a taxonomy that classifies visualisation methods for diachronic semantic shifts with respect to different purposes.
Anthology ID:
2022.sdp-1.10
Volume:
Proceedings of the Third Workshop on Scholarly Document Processing
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Editors:
Arman Cohan, Guy Feigenblat, Dayne Freitag, Tirthankar Ghosal, Drahomira Herrmannova, Petr Knoth, Kyle Lo, Philipp Mayr, Michal Shmueli-Scheuer, Anita de Waard, Lucy Lu Wang
Venue:
sdp
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
89–94
Language:
URL:
https://aclanthology.org/2022.sdp-1.10
DOI:
Bibkey:
Cite (ACL):
Raef Kazi, Alessandra Amato, Shenghui Wang, and Doina Bucur. 2022. Visualisation Methods for Diachronic Semantic Shift. In Proceedings of the Third Workshop on Scholarly Document Processing, pages 89–94, Gyeongju, Republic of Korea. Association for Computational Linguistics.
Cite (Informal):
Visualisation Methods for Diachronic Semantic Shift (Kazi et al., sdp 2022)
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PDF:
https://aclanthology.org/2022.sdp-1.10.pdf