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The fourth V, as in evolution: How evolutionary linguistics can contribute to data science

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dc.contributor.author Pokornowski, Maciej
dc.date.accessioned 2015-04-09T12:43:14Z
dc.date.available 2015-04-09T12:43:14Z
dc.date.issued 2015-01-31
dc.identifier.citation Theoria et Historia Scientiarum, Vol. 11, pp. 45-62
dc.identifier.issn 0867-4159
dc.identifier.other doi:10.12775/ths-2014-003
dc.identifier.uri http://repozytorium.umk.pl/handle/item/2651
dc.description.abstract The paper explores the importance of closer interaction between data science and evolutionary linguistics, pointing to the potential benefits for both disciplines. In the context of big data, the microblogging social networking service – Twitter – can be treated as a source of empirical input for analyses in the field of language evolution. In an attempt to utilize this kind of disciplinary interplay, I propose a model, which constitutes an adaptation of the Iterated Learning framework, for investigating the glossogenetic evolution of sublanguages.  
dc.language.iso eng
dc.rights Attribution-NoDerivs 3.0 Poland
dc.rights info:eu-repo/semantics/openAccess
dc.rights.uri http://creativecommons.org/licenses/by-nd/3.0/pl/
dc.subject Data science
dc.subject evolutionary linguistics
dc.subject natural language processing
dc.subject Twitter
dc.subject glossogeny
dc.subject Iterated Learning framework
dc.title The fourth V, as in evolution: How evolutionary linguistics can contribute to data science
dc.type info:eu-repo/semantics/article


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