Diachronic word embeddings and semantic shifts: a survey
Andrey Kutuzov, Lilja Øvrelid, Terrence Szymanski, Erik Velldal
Abstract
Recent years have witnessed a surge of publications aimed at tracing temporal changes in lexical semantics using distributional methods, particularly prediction-based word embedding models. However, this vein of research lacks the cohesion, common terminology and shared practices of more established areas of natural language processing. In this paper, we survey the current state of academic research related to diachronic word embeddings and semantic shifts detection. We start with discussing the notion of semantic shifts, and then continue with an overview of the existing methods for tracing such time-related shifts with word embedding models. We propose several axes along which these methods can be compared, and outline the main challenges before this emerging subfield of NLP, as well as prospects and possible applications.- Anthology ID:
- C18-1117
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Emily M. Bender, Leon Derczynski, Pierre Isabelle
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1384–1397
- Language:
- URL:
- https://aclanthology.org/C18-1117
- DOI:
- Cite (ACL):
- Andrey Kutuzov, Lilja Øvrelid, Terrence Szymanski, and Erik Velldal. 2018. Diachronic word embeddings and semantic shifts: a survey. In Proceedings of the 27th International Conference on Computational Linguistics, pages 1384–1397, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- Diachronic word embeddings and semantic shifts: a survey (Kutuzov et al., COLING 2018)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/C18-1117.pdf