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

dc.contributor.authorPokornowski, Maciejpl
dc.date.accessioned2015-04-09T12:43:14Z
dc.date.available2015-04-09T12:43:14Z
dc.date.issued2015-01-31pl
dc.description.abstractThe 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.  en
dc.identifier.citationTheoria et Historia Scientiarum, Vol. 11, pp. 45-62pl
dc.identifier.issn0867-4159pl
dc.identifier.otherdoi:10.12775/ths-2014-003pl
dc.identifier.urihttp://repozytorium.umk.pl/handle/item/2651
dc.language.isoengpl
dc.rightsAttribution-NoDerivs 3.0 Polandpl
dc.rightsinfo:eu-repo/semantics/openAccesspl
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/pl/pl
dc.subjectData scienceen
dc.subjectevolutionary linguisticsen
dc.subjectnatural language processingen
dc.subjectTwitteren
dc.subjectglossogenyen
dc.subjectIterated Learning frameworken
dc.titleThe fourth V, as in evolution: How evolutionary linguistics can contribute to data sciencepl
dc.typeinfo:eu-repo/semantics/articlepl

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