Data-intensive investigations of English /

"Illustrated with case studies throughout, this book shows that digital tools can provide exciting, novel answers to old questions in English linguistics. With an emphasis on methodological transparency, this book is essential reading for both scholars and students working in English linguistic...

Full description

Bibliographic Details
Other Authors: Laitinen, Mikko (Editor), Rautionaho, Paula (Editor)
Format: Book
Language:English
Published: Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2026.
Series:Studies in English language.
Subjects:
Table of Contents:
  • Data-intensive approaches to English linguistics / Mikko Laitinen, Paula Rautionaho and Irene Taipale
  • What big data tells us about American English phonetics / William A. Kretzschmar, Jr., Michael Olsen, Rachel Olsen and Katherine Ireland
  • Do you reckon? Creating and testing a corpus of spoken Southern American English from the Digital Archive of Southern Speech (1970-1983) / Keiko Bridwell and Katherine Ireland
  • 'Scots for the masses'? Utilising a novel data-analysis facility to statistically explore late modern Scots in the Digitised Chapbooks Collection / Sarah van Eyndhoven, Lisa Gotthard and Rosa Filgueira
  • Combining collocation measures and distributional semantics to detect idioms / Gerold Schneider
  • Using data-intensive methods for unlocking expressiveness in word-formation: the case of English name blending / Sabine Arndt-Lappe, Natalia Beliaeva and Audrey Martin
  • Modal verb usage across native and non-native Englishes: a variationist analysis / Paula Rautionaho and Lea Meriläinen
  • Bayesian multivariate analysis of complement selection: subject-control complements of the verb fear / Juho Ruohonen and Juhani Rudanko
  • Statistical modelling of syntactic complexity of English academic texts: syntactic predictors of rhetorical sections / Maryam Nasseri
  • Implications of the replication crisis: some suggestions to improve reproducibility and transparency in data-intensive corpus linguistics / Martin Schweinberger.