000			02534nam a22002535i 4500
001			138414
003			ISI Library, Kolkata
005			20190425124617.0
008			170727s2017 nyu 000 0 eng
020			_a9783319645704
040			_aISI Library
082	0	4	_a410.188 _223 _bD441
100	1		_aDesagulier, Guillaume, _eauthor
245	1	0	_aCorpus linguistics and statistics with R : _bintroduction to quantitative methods in linguistics / _cGuillaume Desagulier.
260			_aCham : _bSpringer, _c2017.
300			_axiii, 353 pages : _billustrations (some color) ; _c27 cm.
490	0		_aQuantitative methods in the humanities and social sciences
504			_aIncludes bibliographical references and index.
505	0		_a1. Introduction.- 2. R Fundamentals.- 3. Digital Corpora.- 4. Processing and Manipulating Character Strings.- 5. Applied Character String Processing.- 6. Summary Graphics for Frequency Data.- 7. Descriptive Statistics.- 8. Notions of Statistical Testing.- 9. Association and Productivity.- 10. Clustering Methods.
520			_aThis book examines empirical linguistics from a theoretical linguist?s perspective. It provides both a theoretical discussion of what quantitative corpus linguistics entails and detailed, hands-on, step-by-step instructions to implement the techniques in the field. The statistical methodology and R-based coding from this book teach readers the basic and then more advanced skills to work with large data sets in their linguistics research and studies. Massive data sets are now more than ever the basis for work that ranges from usage-based linguistics to the far reaches of applied linguistics. This book presents much of the methodology in a corpus-based approach. However, the corpus-based methods in this book are also essential components of recent developments in sociolinguistics, historical linguistics, computational linguistics, and psycholinguistics. Material from the book will also be appealing to researchers in digital humanities and the many non-linguistic fields that use textual data analysis and text-based sensorimetrics. Chapters cover topics including corpus processing, frequencing data, and clustering methods. Case studies illustrate each chapter with accompanying data sets, R code, and exercises for use by readers. This book may be used in advanced undergraduate courses, graduate courses, and self-study.
650		0	_aCorpora (Linguistics)
650		0	_aR (Computer program language)
942			_2ddc _cBK
999			_c427597 _d427597