With datafication and deep mediatization (Hepp 2020), digital data have become an inherent part of communication across all societal domains. An increasing number of scholars propose new methodologies including creative, inventive, and artistic methods among others. These should add to the traditional research designs, struggling to grasp the processual character and fluidity of socio-technical data assemblages (Law 2004:4, Kitchin 2014). While a broad variety of empirical and methodological work with a focus on datafication and digital data emerges, a methodological conceptualisation is yet lacking.
My monographic doctoral thesis maps out the field of empirical datafication scholarship with particular focus on applied research methods and the concepts of datafication they produce.
My thesis expands on the concept of methods performativity (Law 2004, Barad 2007, Mol 2002, Savage 2013, Law and Ruppert 2013) that methods assemblages (Law, 2004) of studying datafication are a part of the datafied society and co-produce it. The focus of my investigation is in particular on empirical research within social sciences. I consider methods assemblages empirically as ordering and associating of human (e.g. researchers, researched communities or individuals, further stakeholders such as policy-makers) and non-human actors (e.g. documents, research tools, things and matters relevant in the particular research situation). With my analysis, I identify three kinds of methods assemblages. Central differences between the methods assemblages concern 1) what socio-technical processes are being addressed with these assemblages (what are we talking about when talking about datafication), 2) the extent of collectivity of actors involved in datafication processes, and 3) whether the actors addressed in empirical research are those facing implications of or those enabling datafication processes.
With my thesis, I contribute to the domain of critical data studies by reflecting on the methods performativity in datafication scholarship, by attending to the performativity of methods as methodological strength rather than challenge, and, finally, by developing a heuristic for methodological sensitivity towards multiple elements of datafication processes and methods assemblages applied to study these.