mlsanityData to 14 Oct 2026

DUKweb: Diachronic word representations from the UK Web Archive corpus

arXiv 2107.01076 ↗First posted 2 Jul 2021cs.CL cs.DL cs.LGcited by 0

Not on the map. Why?

Abstract (arXiv)

Lexical semantic change (detecting shifts in the meaning and usage of words) is an important task for social and cultural studies as well as for Natural Language Processing applications. Diachronic word embeddings (time-sensitive vector representations of words that preserve their meaning) have become the standard resource for this task. However, given the significant computational resources needed for their generation, very few resources exist that make diachronic word embeddings available to the scientific community. In this paper we present DUKweb, a set of large-scale resources designed for the diachronic analysis of contemporary English. DUKweb was created from the JISC UK Web Domain Dataset (1996-2013), a very large archive which collects resources from the Internet Archive that were hosted on domains ending in `.uk'. DUKweb consists of a series word co-occurrence matrices and two types of word embeddings for each year in the JISC UK Web Domain dataset. We show the reuse potential of DUKweb and its quality standards via a case study on word meaning change detection.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 49 references that are in the map. First posted on arXiv 2 Jul 2021.

Builds on

14 of 49 references.

References · 14

  1. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  2. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,474
  3. 2016Enriching Word Vectors with Subword Informationcited by 1,583
  4. 2017Word Translation Without Parallel Datacited by 487
  5. 2017Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypescited by 253
  6. 2016Diachronic Word Embeddings Reveal Statistical Laws of Semantic Changecited by 221
  7. 2020SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detectioncited by 108
  8. 2018Diachronic word embeddings and semantic shifts: a surveycited by 92
  9. 2014Statistically Significant Detection of Linguistic Changecited by 82
  10. 2016Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Changecited by 63
  11. 2018Survey of Computational Approaches to Lexical Semantic Changecited by 62
  12. 2014Temporal Analysis of Language through Neural Language Modelscited by 54
2 more
  1. 2019A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domainscited by 31
  2. 2018A Discriminative Latent-Variable Model for Bilingual Lexicon Inductioncited by 8

Built on by

Not cited yet.