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English verb regularization in books and tweets
The English language has evolved dramatically throughout its lifespan, to the extent that a modern speaker of Old English would be incomprehensible without translation. One concrete indicator of this process is the movement from irregular to regular (-ed) forms for the past tense of verbs. In this s...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6310258/ https://www.ncbi.nlm.nih.gov/pubmed/30592735 http://dx.doi.org/10.1371/journal.pone.0209651 |
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author | Gray, Tyler J. Reagan, Andrew J. Dodds, Peter Sheridan Danforth, Christopher M. |
author_facet | Gray, Tyler J. Reagan, Andrew J. Dodds, Peter Sheridan Danforth, Christopher M. |
author_sort | Gray, Tyler J. |
collection | PubMed |
description | The English language has evolved dramatically throughout its lifespan, to the extent that a modern speaker of Old English would be incomprehensible without translation. One concrete indicator of this process is the movement from irregular to regular (-ed) forms for the past tense of verbs. In this study we quantify the extent of verb regularization using two vastly disparate datasets: (1) Six years of published books scanned by Google (2003–2008), and (2) A decade of social media messages posted to Twitter (2008–2017). We find that the extent of verb regularization is greater on Twitter, taken as a whole, than in English Fiction books. Regularization is also greater for tweets geotagged in the United States relative to American English books, but the opposite is true for tweets geotagged in the United Kingdom relative to British English books. We also find interesting regional variations in regularization across counties in the United States. However, once differences in population are accounted for, we do not identify strong correlations with socio-demographic variables such as education or income. |
format | Online Article Text |
id | pubmed-6310258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-63102582019-01-08 English verb regularization in books and tweets Gray, Tyler J. Reagan, Andrew J. Dodds, Peter Sheridan Danforth, Christopher M. PLoS One Research Article The English language has evolved dramatically throughout its lifespan, to the extent that a modern speaker of Old English would be incomprehensible without translation. One concrete indicator of this process is the movement from irregular to regular (-ed) forms for the past tense of verbs. In this study we quantify the extent of verb regularization using two vastly disparate datasets: (1) Six years of published books scanned by Google (2003–2008), and (2) A decade of social media messages posted to Twitter (2008–2017). We find that the extent of verb regularization is greater on Twitter, taken as a whole, than in English Fiction books. Regularization is also greater for tweets geotagged in the United States relative to American English books, but the opposite is true for tweets geotagged in the United Kingdom relative to British English books. We also find interesting regional variations in regularization across counties in the United States. However, once differences in population are accounted for, we do not identify strong correlations with socio-demographic variables such as education or income. Public Library of Science 2018-12-28 /pmc/articles/PMC6310258/ /pubmed/30592735 http://dx.doi.org/10.1371/journal.pone.0209651 Text en © 2018 Gray et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Gray, Tyler J. Reagan, Andrew J. Dodds, Peter Sheridan Danforth, Christopher M. English verb regularization in books and tweets |
title | English verb regularization in books and tweets |
title_full | English verb regularization in books and tweets |
title_fullStr | English verb regularization in books and tweets |
title_full_unstemmed | English verb regularization in books and tweets |
title_short | English verb regularization in books and tweets |
title_sort | english verb regularization in books and tweets |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6310258/ https://www.ncbi.nlm.nih.gov/pubmed/30592735 http://dx.doi.org/10.1371/journal.pone.0209651 |
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