Book contents
- The Cambridge Handbook of English Corpus Linguistics
- Cambridge Handbooks in Language and Linguistics
- The Cambridge Handbook of English Corpus Linguistics
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Major Corpora Cited in the Handbook
- Introduction
- Part I Methodological Considerations
- 1 Corpus Representativeness
- 2 Corpus Tools and Methods
- 3 Quantitative Designs and Statistical Techniques
- Part II Corpus Analysis of Linguistic Characteristics
- Part III Corpus Analysis of Varieties
- Part IV Other Applications of Corpus Analysis
- Index
- References
1 - Corpus Representativeness
from Part I - Methodological Considerations
Published online by Cambridge University Press: 08 July 2026
Book contents
- The Cambridge Handbook of English Corpus Linguistics
- Cambridge Handbooks in Language and Linguistics
- The Cambridge Handbook of English Corpus Linguistics
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Major Corpora Cited in the Handbook
- Introduction
- Part I Methodological Considerations
- 1 Corpus Representativeness
- 2 Corpus Tools and Methods
- 3 Quantitative Designs and Statistical Techniques
- Part II Corpus Analysis of Linguistic Characteristics
- Part III Corpus Analysis of Varieties
- Part IV Other Applications of Corpus Analysis
- Index
- References
Summary
Representativeness is a critical consideration in corpus linguistics as it ensures that the linguistic analyses conducted on a corpus can yield valid and generalizable insights about the target domain. Without adequate consideration for representativeness, findings may be skewed, thereby undermining the reliability of any conclusions drawn. Despite its importance, many corpus-based studies neglect planning for and evaluation of representativeness, which poses limitations to the accuracy and applicability of their results. Although corpus size has been recognized as a determinant of representativeness, domain analysis is an equally important element that has not received as much attention. This chapter utilizes the model of corpus representativeness proposed by Egbert, Biber, and Gray (2022), which advocates for a detailed approach to both domain analysis and sample planning. The model, which is rooted in statistical and logical rigor, underscores the importance of minimizing coverage and selection biases. The chapter applies this model in a case study on constructing a corpus of AI-simulated human conversations. By following the model, the case study illustrates the processes of domain specification, operationalization, and sampling to achieve a high level of representativeness for the corpus.
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- The Cambridge Handbook of English Corpus Linguistics , pp. 13 - 35Publisher: Cambridge University PressPrint publication year: 2026
References
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