Qualitative Text Comparative Analysis (QTCA): A mixed-method approach to large text data

Existing analytical approaches to large-scale text data have prompted concerns about the theoretical meaning of patterns, relationships, or identified constructs and emphasize new analyses in creating meaning from large amounts of unstructured text data. On their own, methods such as Computer-Aided Text Analysis and Qualitative Comparative Analysis cannot resolve these issues as they either lack the means to create configurations or grasp meaning within large bodies of text data. We, therefore, propose a methodological approach that we call Qualitative Text Comparative Analysis (QTCA), combining Computer-Aided Text Analysis and Qualitative Comparative Analysis. Rooted in critical realism, QTCA iterates between theory and empirics, structurally generating deep insights from texts. We propose a four-step road map for engaging in QTCA as a general guide for scholars interested in understanding complex causal conditions using large amounts of text.