Frequency, dispersion, association, and keyness : revising and tupleizing corpus-linguistic measures /

"This book is an attempt to revisit the main specifically corpus-linguistic statistics/measures the field has been relying on for decades: frequency, dispersion, association, and keyness. The book first discusses the purpose of these measures and how these have been measured. Then, the book mak...

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Hlavní autor: Gries, Stefan Thomas, 1970- (Autor)
Typ dokumentu: Kniha
Jazyk:Angličtina
Vydáno: Amsterdam : John Benjamins Publishing Company, [2024]
Edice:Studies in corpus linguistics ; volume 115
Témata:
On-line přístup:Elektronická verze přístupná pouze pro studenty a pracovníky MU
Příbuzné jednotky:Tištěná verze:: Frequency, dispersion, association, and keyness.
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245 1 0 |a Frequency, dispersion, association, and keyness :  |b revising and tupleizing corpus-linguistic measures /  |c Stefan Th. Gries 
264 1 |a Amsterdam :  |b John Benjamins Publishing Company,  |c [2024] 
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505 0 |a Chapter 1 Introduction -- Acknowledgements -- Chapter 2 A review -- Chapter 3 Unification of measures -- Chapter 4 The role, and the 'partialing out', of frequency -- Chapter 5 Tupleization -- Chapter 6 What should be next 
520 |a "This book is an attempt to revisit the main specifically corpus-linguistic statistics/measures the field has been relying on for decades: frequency, dispersion, association, and keyness. The book first discusses the purpose of these measures and how these have been measured. Then, the book makes three main proposals: First, that many measures of dispersion, association, and keyness are too confounded with frequency and how to 'take frequency out of them' to obtain conceptually cleaner / more interpretable measures. Second, that many existing measures can be replaced by the simple information-theoretic measure of the Kullback-Leibler divergence and that it, too, can have frequency 'removed' from it. Third, that corpus linguistics should abandon the tradition of trying to describe our findings with a single number and adopt a tupleization approach instead, where we use several separate dimensions of information for description and interpretation. The book is written in an informal, hands-on style and comes with its own R package featuring functions, example data, and several thousand lines of code exemplifying all applications"  |9 eng 
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