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A69 Phylodynamics of language evolution

We used Bayesian evolutionary analysis to study linguistic data and infer phylogenetic trees of language evolution. Languages were encoded as binary strings indicating the presence or absence of members of cognate classes, the equivalence of classes of words with similar meaning, and shared ancestry...

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Detalles Bibliográficos
Autores principales: Hoffmann, K, Kühnert, D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6735743/
http://dx.doi.org/10.1093/ve/vez002.068
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author Hoffmann, K
Kühnert, D
author_facet Hoffmann, K
Kühnert, D
author_sort Hoffmann, K
collection PubMed
description We used Bayesian evolutionary analysis to study linguistic data and infer phylogenetic trees of language evolution. Languages were encoded as binary strings indicating the presence or absence of members of cognate classes, the equivalence of classes of words with similar meaning, and shared ancestry. These strings formed the alignment data used to compute the posterior likelihood of a tree with respect to Bayes’ formula. Informative priors are crucial for testing hypotheses regarding the age of common ancestry and divergence times and should include as much available information as possible. Here, we investigated the birth–death process as a method to construct tree priors specifically suitable for modeling the evolution of cognate data. To test these models, we will use a dataset of the languages from Vanuatu, an island nation featuring world’s highest language density.
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spelling pubmed-67357432019-09-16 A69 Phylodynamics of language evolution Hoffmann, K Kühnert, D Virus Evol Abstract Overview We used Bayesian evolutionary analysis to study linguistic data and infer phylogenetic trees of language evolution. Languages were encoded as binary strings indicating the presence or absence of members of cognate classes, the equivalence of classes of words with similar meaning, and shared ancestry. These strings formed the alignment data used to compute the posterior likelihood of a tree with respect to Bayes’ formula. Informative priors are crucial for testing hypotheses regarding the age of common ancestry and divergence times and should include as much available information as possible. Here, we investigated the birth–death process as a method to construct tree priors specifically suitable for modeling the evolution of cognate data. To test these models, we will use a dataset of the languages from Vanuatu, an island nation featuring world’s highest language density. Oxford University Press 2019-08-22 /pmc/articles/PMC6735743/ http://dx.doi.org/10.1093/ve/vez002.068 Text en © Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access publication distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Abstract Overview
Hoffmann, K
Kühnert, D
A69 Phylodynamics of language evolution
title A69 Phylodynamics of language evolution
title_full A69 Phylodynamics of language evolution
title_fullStr A69 Phylodynamics of language evolution
title_full_unstemmed A69 Phylodynamics of language evolution
title_short A69 Phylodynamics of language evolution
title_sort a69 phylodynamics of language evolution
topic Abstract Overview
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6735743/
http://dx.doi.org/10.1093/ve/vez002.068
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