Data and Methods in Corpus Linguistics
eBook - PDF

Data and Methods in Corpus Linguistics

Comparative Approaches

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Data and Methods in Corpus Linguistics

Comparative Approaches

About this book

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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Yes, you can access Data and Methods in Corpus Linguistics by Ole Schützler,Julia Schlüter in PDF and/or ePUB format, as well as other popular books in Languages & Linguistics & Linguistics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half-title page
  3. Title page
  4. Copyright page
  5. Contents
  6. List of Figures
  7. List of Tables
  8. List of Contributors
  9. Acknowledgements
  10. Introduction: Comparative Approaches to Data and Methods in Corpus Linguistics
  11. Part I Corpus Dimensions and the Viability of Methodological Approaches
  12. Part II Selection, Calibration and Preparation of Corpus Data
  13. Part III Perspectives on Multifactorial Methods
  14. Part IV Applications of Classification-Based Approaches
  15. Index