New publication in Big Data & Society: Computational grounded theory revisited

Assistant professor and DISTRACT team member Hjalmar Bang Carlsen has recently published (with postdoc Snorre Ralund), an article in the journal Big Data & Society entitled Computational grounded theory revisited: From computer-led to computer-assisted text analysis. 

The article is part of an upcoming special issue in Big Data & Society edited by DISTRACT PI, Morten Axel Pedersen, entitled "Machine Anthropology". 

ABSTRACT

The size and variation in both meaning-making and populations that characterize much contemporary text data demand research processes that support both discovery, interpretation and measurement. We assess one dominant strategy within the social sciences that takes a computer-led approach to text analysis. The approach is coined computational grounded theory. This strategy, we argue, relies on a set of unwarranted assumptions, namely, that unsupervised models return natural clusters of meaning, that the researcher can understand text with limited immersion and that indirect validation is sufficient for ensuring unbiased and precise measurement. In response to this criticism, we develop a framework that is computer assisted. We argue that our reformulation of computational grounded theory better aligns with the principles within grounded theory, anthropological theory generation and ethnography.