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9781108499644: Data and Methods in Corpus Linguistics: Comparative Approaches

Sinopsis

Corpus linguistics continues to be a vibrant methodology applied across highly diverse fields of research in the language sciences. With the current steep rise in corpus sizes, computational power, statistical literacy and multi-purpose software tools, and inspired by neighbouring disciplines, approaches have diversified to an extent that calls for an intensification of the accompanying critical debate. Bringing together a team of leading experts, this book follows a unique design, comparing advanced methods and approaches current in corpus linguistics, to stimulate reflective evaluation and discussion. Each chapter explores the strengths and weaknesses of different datasets and techniques, presenting a case study and allowing readers to gauge methodological options in practice. Contributions also provide suggestions for further reading, and data and analysis scripts are included in an online appendix. This is an important and timely volume, and will be essential reading for any linguist interested in corpus-linguistic approaches to variation and change.

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Acerca de los autores

Ole Schützler is Professor for Varieties of English at Leipzig University. Mostly working within the frameworks of quantitative sociolinguistics/sociophonetics and corpus linguistics, he takes a general interest in synchronic and diachronic variation and change in English with a special focus on Scottish Englishes.

Julia Schlüter is Associate Professor for English Linguistics at the University of Bamberg. Her research interests lie in the areas of phonological and grammatical variation in British and American English past and present, empirical – especially corpus-based – methodologies, and applications of linguistic insights and techniques to the teaching of English.

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9781108731034: Data and Methods in Corpus Linguistics: Comparative Approaches

Edición Destacada

ISBN 10:  1108731031 ISBN 13:  9781108731034
Editorial: Cambridge University Press, 2025
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