How might 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. Designed for the analysis of voluminous textual data, it offers a recognised 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. In other words, CADS can assist researchers in revealing the social dynamics of the text. Bringing 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. Focused 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’.
