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In:Quantitative Methods in Multilingual Acquisition and Processing
Edited by Gabrielle Klassen and John W. Schwieter
[Research Methods in Applied Linguistics 16] 2026
► pp. 28–55

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Chapter 3
Using corpora and variationist approaches to make inferences about language representation

Published online: 26 March 2026
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https://doi.org/10.1075/rmal.16.03esc
Abstract
As interest in usage-based approaches to multilingualism has grown, researchers have increasingly turned to large data sets (i.e., corpora) of actual language usage to study linguistic phenomena. Exploring multilingual or multidialectal corpora can shed important light on multilingual acquisition and processing, extending our understanding of how speakers develop and maintain or lose languages over time, how their languages vary and change, and how languages interact within the mind of the speaker and within a multilingual community. While English has traditionally dominated the field of corpus linguistics, there has been a growing recognition of the need to develop corpora and tools for other languages to assure that research findings sufficiently consider linguistic diversity (O’Keeffe & McCarthy, 2010). While corpus research in recent years has expanded to include a wider variety of languages, there are still few resources that guide researchers to engage with these corpora. This chapter serves as a theoretical and practical resource for researchers interested in using corpora to study multilingualism — particularly language variation and acquisition — with special attention paid to the two most widely-spoken languages aside from English: Spanish and Mandarin Chinese. We discuss how to use corpora to answer questions of bi/multilingual language representations and linguistic theory, including how to extract patterns in large corpora (e.g., tokenizing, part of speech tagging, error tagging) and how to analyze these patterns using logistic regression and mixed-effects modeling. We review research questions about why and how languages vary when in contact with other languages, either internally (within a single mind) or externally (in a community). Lastly, we include guidelines and best practices for the development and analysis of new and existing corpora.
Article outline
  • 3.1Introduction
  • 3.2Corpus linguistics, variation, and the benefits of quantitative analysis
    • 3.2.1What is a corpus?
    • 3.2.2Corpus types, characteristics, and objectives
    • 3.2.3Variation
  • 3.3How to extract patterns using corpora
    • 3.3.1Corpus analysis
      • 3.3.1.1Tokenizing and part of speech tagging
      • 3.3.1.2Error tagging and other manual annotations
      • 3.3.1.3Off-the-shelf tools
      • 3.3.1.4Logistic regression
      • 3.3.1.5Mixed-effects modeling
      • 3.3.1.6Multi-dimensional framework
  • 3.4Looking ahead
    • 3.4.1Developing new corpora
    • 3.4.2Future directions for analyses of existing corpora
      • 3.4.2.1Phonetic analyses
      • 3.4.2.2Task variables
      • 3.4.2.3Other methodological approaches
  • 3.5Conclusion
  • References
References (101)
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