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Corpus linguistics is not just for linguists

Considering the potential of computer-based corpus methods for library and information science research
Authors: Lynne Bowker;

Corpus linguistics is not just for linguists

Abstract

Purpose The purpose of this paper is to generate awareness of and interest in the techniques used in computer-based corpus linguistics, focusing on their methodological implications for research in library and information science (LIS). Design/methodology/approach This methodology paper provides an overview of computer-based corpus linguistics, describes the main techniques used in this field, assesses its strengths and weaknesses, and presents examples to illustrate the value of corpus linguistics to LIS research. Findings Overall, corpus-based techniques are simple, yet powerful, and they support both quantitative and qualitative analyses. While corpus methods alone may not be sufficient for research in LIS, they can be used to complement and to help triangulate the findings of other methods. Corpus linguistics techniques also have the potential to be exploited more fully in LIS research that involves a higher degree of automation (e.g. recommender systems, knowledge discovery systems, and text mining). Practical implications Numerous LIS researchers have drawn attention to the lack of diversity in research methods used in this field, and suggested that approaches permitting mixed methods research are needed. If LIS researchers learn about the potential of computer-based corpus methods, they can diversify their approaches. Originality/value Over the past quarter century, corpus linguistics has established itself as one of the main methods used in the field of linguistics, but its potential has not yet been realized by researchers in LIS. Corpus linguistics tools are readily available and relatively straightforward to apply. By raising awareness about corpus linguistics, the author hopes to make these techniques available as additional tools in the LIS researcher’s methodological toolbox, thus broadening the range of methods applied in this field.

Keywords

Methods, Languages, Software tools, Computer applications, 420, Research methods, Techniques

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Top 10%
Top 10%
Green
hybrid