ABSTRACT
This chapter aims to illuminate the exploratory and explanatory power of using multiple data sets, or in other words, data triangulation in a corpus-assisted discourse study (CADS). It focuses on the benefits of comparisons across contexts, to which data triangulation ultimately lends itself. Investigating how a discursive phenomenon behaves in multiple contexts using multiple data sets can therefore help the researcher not only explore recontextualisations and intertextuality but also uncover the playgrounds of ideologies and help understand the mechanics of ideological work in and through discourse. The modifiers of depression indicate the extent to which the biomedical model of depression is accepted and recontextualised from medical texts across media and lay accounts of postnatal depression (PND). Using multiple data sets allowed the authors to gain a much more profound understanding of discourses around PND by reducing some of the blind spots that often lurk in discourse analysis based on a single set of data.
