Heaps’ Law and Heaps functions in tagged texts: evidences of their linguistic relevance

cnea.tipodocumentoARTÍCULO CIENTÍFICO
dc.contributor.authorChacoma, A.
dc.contributor.authorZanette, Damian Horacio
dc.date.accessioned2025-03-19T15:34:02Z
dc.date.available2025-03-19T15:34:02Z
dc.date.issued2020
dc.description.abstractWe study the relationship between vocabulary size and text length in a corpus of 75 literary works in English, authored by six writers, distinguishing between the contributions of three grammatical classes (or ‘tags,’ namely, nouns, verbs and others), and analyse the progressive appearance of new words of each tag along each individual text. We find that, as prescribed by Heaps’ Law, vocabulary sizes and text lengths follow a well-defined power-law relation. Meanwhile, the appearance of new words in each text does not obey a power law, and is on the whole well described by the average of random shufflings of the text. Deviations from this average, however, are statistically significant and show systematic trends across the corpus. Specifically, we find that the appearance of new words along each text is predominantly retarded with respect to the average of random shufflings. Moreover, different tags add systematically distinct contributions to this tendency, with verbs and others being respectively more and less retarded than the mean trend, and nouns following instead the overall mean. These statistical systematicities are likely to point to the existence of linguistically relevant information stored in the different variants of Heaps’ Law, a feature that is still in need of extensive assessment.
dc.description.institutionalaffiliationFil.: Zanette, Damian Horacio Comisión Nacional de Energía Atómica. Instituto Balseiro; Universidad Nacional de Cuyo, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina
dc.description.institutionalaffiliationexternalFil.: Chacoma, A Instituto de Física Enrique Gaviola. Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina; Universidad Nacional de Córdoba, Argentina
dc.format.extent1-15 p.
dc.format.extentapplication/pdf
dc.identifier.doihttps://doi.org/10.1098/rsos.200008
dc.identifier.urihttps://nuclea.cnea.gob.ar/handle/20.500.12553/6181
dc.language.ISO639-3eng
dc.publisherRoyal Society
dc.relation.ispartofRoyal Society Open Science; Vol. 7 N° 3 (2020), pp. 1-15
dc.rights.accesslevelinfo:eu-repo/semantics/openAccess
dc.rights.licenseCreative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subject.keywordREGULARIDADES DEL LENGIAJE
dc.subject.keywordLEY DE HEAPS
dc.subject.keywordTEXTOS ETIQUETADOS
dc.subject.keywordCLASES GRAMATICALES
dc.subject.keywordANOMALIAS ESTADISTICAS
dc.subject.keywordLANGUAGE REGULARITIES
dc.subject.keywordHEAP’S LAW
dc.subject.keywordTAGGED TEXTS
dc.subject.keywordGRAMMATICAL CLASSES
dc.subject.keywordSTATISTICAL ANOMALIES
dc.titleHeaps’ Law and Heaps functions in tagged texts: evidences of their linguistic relevance
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:ar-repo/semantics/artículo
dc.type.versioninfo:eu-repo/semantics/publishedVersion

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