Taking the road less travelled: How corpus-assisted discourse studies can enrich qualitative explorations of large textual datasets

Mathew Gillings, Mark Learmonth*, Gerlinde Mautner

*Corresponding author for this work

Publication: Scientific journalJournal articlepeer-review


How might interpretivist qualitative researchers tackle large data sets consisting of millions or even billions of words? Corpus-assisted discourse studies (CADS) is the approach we explore here. Specifically designed for the analysis of voluminous textual data, it offers a recognized empirical approach for making sense of such data. But it does so within an epistemology that understands language to be central in shaping our understanding of the world around us, so that CADS can assist researchers in revealing the social dynamics of the text – including the ideology and power that is latent in many such corpora. Bringing together the training of applied linguists and a management scholar, we discuss the background to CADS and its differences from text-mining approaches such as topic modelling, which have been more widely used in management studies to date. Focusing on the needs of people who are new to the approach, we then offer a worked example to show CADS’ potential in exploring a management-related corpus. Our paper concludes with a discussion of the strengths and weaknesses of the approach and its potential for future discursively orientated management research – especially in the context of the rise of ‘big data’.
Original languageEnglish
JournalBritish Journal of Management
Publication statusE-pub ahead of print - 1 Mar 2024

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