Book contents
- Data-Intensive Investigations of English
- Studies in English Language
- Data-Intensive Investigations of English
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Acknowledgments
- Chapter 1 Data-Intensive Approaches to English Linguistics
- Chapter 2 What Big Data Tells Us about American English Phonetics
- Chapter 3 Do You Reckon?
- Chapter 4 ‘Scots for the Masses’?
- Chapter 5 Combining Collocation Measures and Distributional Semantics to Detect Idioms
- Chapter 6 Using Data-Intensive Methods for Unlocking Expressiveness in Word Formation
- Chapter 7 Modals of Future Time Reference across Native and Non-native Englishes
- Chapter 8 Bayesian Multivariate Analysis of Complement Selection
- Chapter 9 Statistical Modelling of Syntactic Complexity of English Academic Texts Using Ensemble Machine Learning
- Chapter 10 Implications of the Replication Crisis
- Index
- References
Chapter 1 - Data-Intensive Approaches to English Linguistics
Published online by Cambridge University Press: 03 December 2025
Book contents
- Data-Intensive Investigations of English
- Studies in English Language
- Data-Intensive Investigations of English
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Acknowledgments
- Chapter 1 Data-Intensive Approaches to English Linguistics
- Chapter 2 What Big Data Tells Us about American English Phonetics
- Chapter 3 Do You Reckon?
- Chapter 4 ‘Scots for the Masses’?
- Chapter 5 Combining Collocation Measures and Distributional Semantics to Detect Idioms
- Chapter 6 Using Data-Intensive Methods for Unlocking Expressiveness in Word Formation
- Chapter 7 Modals of Future Time Reference across Native and Non-native Englishes
- Chapter 8 Bayesian Multivariate Analysis of Complement Selection
- Chapter 9 Statistical Modelling of Syntactic Complexity of English Academic Texts Using Ensemble Machine Learning
- Chapter 10 Implications of the Replication Crisis
- Index
- References
Summary
This chapter defines data-intensive research in the context of the English language and explores its prospects. It argues that data intensiveness extends beyond a single digital method or the use of advanced statistical tools; rather it encompasses a broader transformation and fuller integration of digital tools and methods throughout the research process. We also address the potential pitfalls of data fetishism and over-reliance on data, and we draw parallels with the digital transformation in another discipline, specifically biosciences, to illustrate the fundamental changes proposed as a result of digitalization. The lessons learned from other fields underscore the need for increased multi- and interdisciplinary collaboration and the development of broader digital infrastructures. This includes investments in enhanced computing power, robust data management processes, and a greater emphasis on replicability and transparency in reporting methods, data, and analytical techniques.
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- Data-Intensive Investigations of English , pp. 1 - 19Publisher: Cambridge University PressPrint publication year: 2025
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