Beyond Content: Discriminatory Power of Function Words in Text Type Classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15210%2F24%3A73624593" target="_blank" >RIV/61989592:15210/24:73624593 - isvavai.cz</a>
Result on the web
<a href="https://academic.oup.com/dsh/article/39/2/765/7634746?login=true" target="_blank" >https://academic.oup.com/dsh/article/39/2/765/7634746?login=true</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1093/llc/fqae013" target="_blank" >10.1093/llc/fqae013</a>

Result language
angličtina
Original language name
Beyond Content: Discriminatory Power of Function Words in Text Type Classification
Original language description
Our work aims to evaluate the strength of the association between function words and several text types: novels, poems, academic articles, reviews and blog posts, and the accuracy of their classification to these categories, through machine-learning and statistical methods. The principal conclusion is that the types of texts are distinguishable based only on the function words, either by vocabulary or vocabulary diversity. Such findings may impact the techniques of authorship attribution based on function words and text clustering techniques since some function words add information about the text types/genres, in addition to content words.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
60203 - Linguistics

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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