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Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change
William L. Hamilton, Jure Leskovec, Dan Jurafsky, 2016. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
Uses word embeddings trained on texts from different periods to measure how word meanings change, and finds two statistical laws of semantic change.
What it's used for here
The inductive-methods survey cites its alignment of embedding spaces for comparing the manuscript's sections.
Cited by on this site 1 record
1 methods surveys
SRCInductive methods
Cite it
Hamilton, W. L., Leskovec, J., & Jurafsky, D. (2016). Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). https://doi.org/10.18653/v1/p16-1141
@article{hamilton2016diachronic,
author = {Hamilton, William L. and Leskovec, Jure and Jurafsky, Dan},
title = {Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change},
journal = {Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
year = {2016},
doi = {10.18653/v1/p16-1141},
url = {https://doi.org/10.18653/v1/p16-1141}
}TY - JOUR TI - Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change AU - Hamilton, William L. AU - Leskovec, Jure AU - Jurafsky, Dan PY - 2016 JO - Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) DO - 10.18653/v1/p16-1141 UR - https://doi.org/10.18653/v1/p16-1141 ER -
Hamilton, William L. et al.. “Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change.” Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2016). https://doi.org/10.18653/v1/p16-1141.