# Hamilton 2016: Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change

> William L. Hamilton, Jure Leskovec, Dan Jurafsky, 2016. 1 records on Mysteries Department cite it. The inductive-methods survey cites its alignment of…

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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.

**Voynich Manuscript** Articledoi: **[10.18653/v1/p16-1141](https://doi.org/10.18653/v1/p16-1141)** Checked against the original0

## 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]

Inductive methods

SRC

## 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
```

[Read it free at doi.org](https://doi.org/10.18653/v1/p16-1141)[PDF stored here · 13 pages](https://mysteriesdept.com/sources/SRC0D8MR5FY3GP1/diachronic-word-embeddings-reveal-statistical-laws-of/pdf)

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