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A diachronic evaluation of gender asymmetry in euphemism

arXiv 2106.02083 ↗First posted 3 Jun 2021cs.CLcited by 4

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Abstract (arXiv)

The use of euphemisms is a known driver of language change. It has been proposed that women use euphemisms more than men. Although there have been several studies investigating gender differences in language, the claim about euphemism usage has not been tested comprehensively through time. If women do use euphemisms more, this could mean that women also lead the formation of new euphemisms and language change over time. Using four large diachronic text corpora of English, we evaluate the claim that women use euphemisms more than men through a quantitative analysis. We assembled a list of 106 euphemism-taboo pairs to analyze their relative use through time by each gender in the corpora. Contrary to the existing belief, our results show that women do not use euphemisms with a higher proportion than men. We repeated the analysis using different subsets of the euphemism-taboo pairs list and found that our result was robust. Our study indicates that in a broad range of settings involving both speech and writing, and with varying degrees of formality, women do not use or form euphemisms more than men.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 7 of its 43 references that are in the map. First posted on arXiv 3 Jun 2021.

Builds on

7 of 43 references.

References · 7

  1. 2016Diachronic Word Embeddings Reveal Statistical Laws of Semantic Changecited by 219
  2. 2020Analysing Lexical Semantic Change with Contextualised Word Representationscited by 92
  3. 2014Statistically Significant Detection of Linguistic Changecited by 82
  4. 2018Survey of Computational Approaches to Lexical Semantic Changecited by 60
  5. 2017Dynamic Word Embeddingscited by 51
  6. 2021Self-Supervised Euphemism Detection and Identification for Content Moderationcited by 24
  7. 2020Pick a Fight or Bite your Tongue: Investigation of Gender Differences in Idiomatic Language Usagecited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 0; 2024: 0; 2025: 0; 2026: 1.

4 papers.