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Estratégias Lexicométricas para Detetar Especificidades Textuais

Lexicometric strategies to detect textual specificities
Authors: Álvaro Iriarte Sanromán; Pablo Gamallo Otero; Alberto Simões 0001;

Estratégias Lexicométricas para Detetar Especificidades Textuais

Abstract

Neste artigo propomo-nos a definir e desenvolver uma estratégia automática para procurar especificidades lexicais dentro de conjuntos de textos utilizando unidades lexicais simples e expressões com várias palavras, ou termos multipalavra (MWE, a sua sigla em inglês). Propomos uma metodologia para o cálculo da divergência de distribuições de lemas e de MWE que permitirá encontrar, automaticamente, diferenças e semelhanças entre textos não anotados. Esta metodologia poderá ser utilizada para posteriormente identificar grupos de textos sobre os quais se procederá a análises quantitativas e qualitativas semiautomáticas e/ou com intervenção humana. Num primeiro teste, utilizamos dois textos de especialidade (da área da pediatria) e um texto literário, presumindo que os textos de especialidade deveriam apresentar maiores divergências relativamente ao texto literário do que entre eles próprios. Como os testes feitos mostraram a tendência esperada, decidimos aplicar a mesma metodologia a um segundo grupo de textos (três conjuntos de entrevistas a visitantes da cidade de Santiago de Compostela).

Countries
Spain, Portugal, Portugal
Keywords

Lexicometry, Kullback-Leibler divergence, Language and Literature, lexicometria, P, P1-1091, Kullback–Leibler divergence, Divergência lexical, Computational Linguistics, Divergencia de Kullback-Leibler, lexical divergence, lexicometry, divergência lexical, Lexicometria, Divergência de Kullback-Leibler, Philology. Linguistics, Lexical divergence, divergencia de Kullback-Leibler, Natural Language Processing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Published in a Diamond OA journal