Abstract
We introduce a simple concept tracking approach to support conceptual history research. Building on the existing practices of conceptual historians, we use dictionaries to identify “anchors”, which represent primary dimensions of meaning of a concept. Then, we create a plot showing how a key concept has evolved over time in a historical corpus in relation to these dimensions. We demonstrate the approach by plotting the change of several key concepts in the COHA corpus.- Anthology ID:
- 2023.lchange-1.9
- Volume:
- Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Nina Tahmasebi, Syrielle Montariol, Haim Dubossarsky, Andrey Kutuzov, Simon Hengchen, David Alfter, Francesco Periti, Pierluigi Cassotti
- Venue:
- LChange
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 87–92
- Language:
- URL:
- https://aclanthology.org/2023.lchange-1.9
- DOI:
- 10.18653/v1/2023.lchange-1.9
- Cite (ACL):
- Jetske Adams, Martha Larson, Jaap Verheul, and Michael Boyden. 2023. Anchors in Embedding Space: A Simple Concept Tracking Approach to Support Conceptual History Research. In Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change, pages 87–92, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Anchors in Embedding Space: A Simple Concept Tracking Approach to Support Conceptual History Research (Adams et al., LChange 2023)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2023.lchange-1.9.pdf