國立虎尾科技大學 |

Data and methods in corpus linguistics = comparative approaches /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data and methods in corpus linguistics/ edited by Ole Schützler, Julia Schlüter.
其他題名:	comparative approaches /
其他作者:	Schlüter, Julia.
出版者:	Cambridge ; New York :Cambridge University Press, : 2022.,
面頁冊數:	xvi, 357 p. :ill., digital ; : 24 cm.;
附註:	Title from publisher's bibliographic system (viewed on 07 Apr 2022).
標題:	Linguistics - Statistical methods. -
電子資源:	https://doi.org/10.1017/9781108589314
ISBN:	9781108589314

Data and methods in corpus linguistics = comparative approaches /
Data and methods in corpus linguisticscomparative approaches /[electronic resource] :edited by Ole Schützler, Julia Schlüter. - Cambridge ; New York :Cambridge University Press,2022. - xvi, 357 p. :ill., digital ;24 cm.

Title from publisher's bibliographic system (viewed on 07 Apr 2022).

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.

ISBN: 9781108589314Subjects--Topical Terms:

808304
Linguistics
--Statistical methods.

LC Class. No.: P128.C68 / D378 2022

Dewey Class. No.: 410.188

Data and methods in corpus linguistics = comparative approaches /
LDR:01926nam a2200241 a 4500 001 1114093
003 UkCbUP
005 20220511092829.0
006 m d
007 cr nn 008maaau
008 231225s2022 enk o 1 0 eng d
020 $a 9781108589314 $q (electronic bk.)
020 $a 9781108499644 $q (hardback)
035 $a CR9781108589314
040 $a UkCbUP $b eng $c UkCbUP $d GP
050 0 0 $a P128.C68 $b D378 2022
082 0 0 $a 410.188 $2 23
090 $a P128.C68 $b D232 2022
245 0 0 $a Data and methods in corpus linguistics $h [electronic resource] : $b comparative approaches / $c edited by Ole Schützler, Julia Schlüter.
260 $a Cambridge ; New York : $b Cambridge University Press, $c 2022.
300 $a xvi, 357 p. : $b ill., digital ; $c 24 cm.
500 $a Title from publisher's bibliographic system (viewed on 07 Apr 2022).
520 $a 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.
650 0 $a Linguistics $x Statistical methods. $3 808304
650 0 $a Corpora (Linguistics) $x Data processing. $3 1426741
700 1 $a Schlüter, Julia. $3 1426740
700 1 $a Schützler, Ole. $3 1426739
856 4 0 $u https://doi.org/10.1017/9781108589314