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  5. Decade-level Word2Vec models from automatically transcribed 19th-century newspapers digitised by the British Library (1800-1919)

Decade-level Word2Vec models from automatically transcribed 19th-century newspapers digitised by the British Library (1800-1919)

Resource type
Dataset
Creator (Person)
Pedrazzini, Nilo
ORCIDORCID logo
Date published
May 2, 2023
Abstract
Word embeddings trained on a 4.2-billion-word corpus of 19th-century British newspapers using Word2Vec and specific parameters. The embeddings are divided into periods of ten years each. Unlike those in this repository, these were not aligned and OCR errors skimmed from the vocabulary. See related GitHub repository for the full documentation: https://github.com/Living-with-machines/DiachronicEmb-BigHistData. Project website (Living with Machines): https://livingwithmachines.ac.uk/
Contributor (person)
Ridge, Mia
ORCIDORCID logo
Contributor (organisation)
British Library
Living with Machines
Project(s)
Living with Machines
Funder
Funder nameAwards
UK Research and Innovation
AH/S01179X/1
Arts and Humanities Research Council
AH/S01179X/1
Version
1
Publisher
Zenodo
Official URL
https://doi.org/10.5281/zenodo.7887305
Related URL
https://zenodo.org/record/7887305
https://github.com/Living-with-machines/DiachronicEmb-BigHistData
https://livingwithmachines.ac.uk/
Licence
https://creativecommons.org/licenses/by/4.0/
DOI
10.5281/zenodo.7887305
Related identifier
IdentifierTypeRelation
10.5281/zenodo.7181682
DOI
iscontinuedby
10.5281/zenodo.7887304
DOI
isversionof
Keywords
word embeddings
word vectors
word2vec
Late Modern English
British newspapers
historical semantics
Collection
Living with Machines
Managed by the British Library and supported by the AHRC

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