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Complexity trade-offs and equi-complexity in natural languages: a meta-analysis

In linguistics, there is little consensus on how to define, measure, and compare complexity across languages. We propose to take the diversity of viewpoints as a given, and to capture the complexity of a language by a vector of measurements, rather than a single value. We then assess the statistical...

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Autores principales: Bentz, Christian, Gutierrez-Vasques, Ximena, Sozinova, Olga, Samardžić, Tanja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: De Gruyter 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234276/
https://www.ncbi.nlm.nih.gov/pubmed/37275745
http://dx.doi.org/10.1515/lingvan-2021-0054
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author Bentz, Christian
Gutierrez-Vasques, Ximena
Sozinova, Olga
Samardžić, Tanja
author_facet Bentz, Christian
Gutierrez-Vasques, Ximena
Sozinova, Olga
Samardžić, Tanja
author_sort Bentz, Christian
collection PubMed
description In linguistics, there is little consensus on how to define, measure, and compare complexity across languages. We propose to take the diversity of viewpoints as a given, and to capture the complexity of a language by a vector of measurements, rather than a single value. We then assess the statistical support for two controversial hypotheses: the trade-off hypothesis and the equi-complexity hypothesis. We furnish meta-analyses of 28 complexity metrics applied to texts written in overall 80 typologically diverse languages. The trade-off hypothesis is partially supported, in the sense that around one third of the significant correlations between measures are negative. The equi-complexity hypothesis, on the other hand, is largely confirmed. While we find evidence for complexity differences in the domains of morphology and syntax, the overall complexity vectors of languages turn out virtually indistinguishable.
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spelling pubmed-102342762023-06-02 Complexity trade-offs and equi-complexity in natural languages: a meta-analysis Bentz, Christian Gutierrez-Vasques, Ximena Sozinova, Olga Samardžić, Tanja Linguist Vanguard Article In linguistics, there is little consensus on how to define, measure, and compare complexity across languages. We propose to take the diversity of viewpoints as a given, and to capture the complexity of a language by a vector of measurements, rather than a single value. We then assess the statistical support for two controversial hypotheses: the trade-off hypothesis and the equi-complexity hypothesis. We furnish meta-analyses of 28 complexity metrics applied to texts written in overall 80 typologically diverse languages. The trade-off hypothesis is partially supported, in the sense that around one third of the significant correlations between measures are negative. The equi-complexity hypothesis, on the other hand, is largely confirmed. While we find evidence for complexity differences in the domains of morphology and syntax, the overall complexity vectors of languages turn out virtually indistinguishable. De Gruyter 2022-10-14 /pmc/articles/PMC10234276/ /pubmed/37275745 http://dx.doi.org/10.1515/lingvan-2021-0054 Text en © 2022 the author(s), published by De Gruyter, Berlin/Boston https://creativecommons.org/licenses/by/4.0/This work is licensed under the Creative Commons Attribution 4.0 International License.
spellingShingle Article
Bentz, Christian
Gutierrez-Vasques, Ximena
Sozinova, Olga
Samardžić, Tanja
Complexity trade-offs and equi-complexity in natural languages: a meta-analysis
title Complexity trade-offs and equi-complexity in natural languages: a meta-analysis
title_full Complexity trade-offs and equi-complexity in natural languages: a meta-analysis
title_fullStr Complexity trade-offs and equi-complexity in natural languages: a meta-analysis
title_full_unstemmed Complexity trade-offs and equi-complexity in natural languages: a meta-analysis
title_short Complexity trade-offs and equi-complexity in natural languages: a meta-analysis
title_sort complexity trade-offs and equi-complexity in natural languages: a meta-analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234276/
https://www.ncbi.nlm.nih.gov/pubmed/37275745
http://dx.doi.org/10.1515/lingvan-2021-0054
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