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%0 Conference Proceedings
%T Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change
%A Hamilton, William L.
%A Leskovec, Jure
%A Jurafsky, Dan
%Y Erk, Katrin
%Y Smith, Noah A.
%S Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2016
%8 August
%I Association for Computational Linguistics
%C Berlin, Germany
%F hamilton-etal-2016-diachronic
%R 10.18653/v1/P16-1141
%U https://aclanthology.org/P16-1141/
%U https://doi.org/10.18653/v1/P16-1141
%P 1489-1501

Markdown (Informal)

[Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change](https://aclanthology.org/P16-1141/) (Hamilton et al., ACL 2016)

• Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change (Hamilton et al., ACL 2016)

ACL

• William L. Hamilton, Jure Leskovec, and Dan Jurafsky. 2016. Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1489–1501, Berlin, Germany. Association for Computational Linguistics.