Words with Consistent Diachronic Usage Patterns are Learned Earlier: A Computational Analysis Using Temporally Aligned Word Embeddings

Cognitive Science 45 (4):e12963 (2021)
  Copy   BIBTEX

Abstract

In this study, we use temporally aligned word embeddings and a large diachronic corpus of English to quantify language change in a data-driven, scalable way, which is grounded in language use. We show a unique and reliable relation between measures of language change and age of acquisition (AoA) while controlling for frequency, contextual diversity, concreteness, length, dominant part of speech, orthographic neighborhood density, and diachronic frequency variation. We analyze measures of language change tackling both the change in lexical representations and the change in the relation between lexical representations and the words with the most similar usage patterns, showing that they capture different aspects of language change. Our results show a unique relation between language change and AoA, which is stronger when considering neighborhood-level measures of language change: Words with more coherent diachronic usage patterns tend to be acquired earlier. The results support theories positing a link between ontogenetic and ethnogenetic processes in language.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 91,592

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Why Can Computers Understand Natural Language?Juan Luis Gastaldi - 2020 - Philosophy and Technology 34 (1):149-214.
Using Predictability for Lexical Segmentation.Çağrı Çöltekin - 2017 - Cognitive Science 41 (7):1988-2021.
LD-Algebras Beyond I0.Vincenzo Dimonte - 2019 - Notre Dame Journal of Formal Logic 60 (3):395-405.

Analytics

Added to PP
2021-04-21

Downloads
11 (#1,130,421)

6 months
5 (#627,481)

Historical graph of downloads
How can I increase my downloads?