Dynamic embedded topic models and change-point detection for exploring literary-historical hypotheses

Hale Sirin, Thomas Lippincott


Abstract
We present a novel combination of dynamic embedded topic models and change-point detection to explore diachronic change of lexical semantic modality in classical and early Christian Latin. We demonstrate several methods for finding and characterizing patterns in the output, and relating them to traditional scholarship in Comparative Literature and Classics. This simple approach to unsupervised models of semantic change can be applied to any suitable corpus, and we conclude with future directions and refinements aiming to allow noisier, less-curated materials to meet that threshold.
Anthology ID:
2024.latechclfl-1.22
Volume:
Proceedings of the 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2024)
Month:
March
Year:
2024
Address:
St. Julians, Malta
Editors:
Yuri Bizzoni, Stefania Degaetano-Ortlieb, Anna Kazantseva, Stan Szpakowicz
Venues:
LaTeCHCLfL | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
231–236
Language:
URL:
https://aclanthology.org/2024.latechclfl-1.22
DOI:
Bibkey:
Cite (ACL):
Hale Sirin and Thomas Lippincott. 2024. Dynamic embedded topic models and change-point detection for exploring literary-historical hypotheses. In Proceedings of the 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2024), pages 231–236, St. Julians, Malta. Association for Computational Linguistics.
Cite (Informal):
Dynamic embedded topic models and change-point detection for exploring literary-historical hypotheses (Sirin & Lippincott, LaTeCHCLfL-WS 2024)
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PDF:
https://aclanthology.org/2024.latechclfl-1.22.pdf
Supplementary material:
 2024.latechclfl-1.22.SupplementaryMaterial.zip
Video:
 https://aclanthology.org/2024.latechclfl-1.22.mp4