We propose a set of methodological principles and strategies for the use of trace data, i.e., data capturing performances carried out on or via information systems, often at a fine level of detail. Trace data comes with a number of methodological and theoretical challenges associated with the inseparable nature of the social and material. Drawing on Haraway and Barad’s distinctions among refraction, reflection and diffraction, we compare three approaches to trace data analysis. We argue that a diffractive methodology allows us to explore how trace data are not given but created though construction of a research apparatus to study trace data. By focusing on the diffractive ways in which traces ripple through an apparatus, it is possible to explore some of the taken-for-granted, invisible dynamics of sociomateriality. Equally, important this approach allows us to describe what and when distinctions within entwined phenomena emerge in the research process. Empirically, we illustrate the guiding principles and strategies by analyzing trace data from Gravity Spy, a crowdsourced citizen science project on Zooniverse. We conclude by suggesting that a diffractive methodology may help us draw together quantitative and qualitative research practices in new and productive ways that also raises interesting design questions.
|Original language||English (US)|
|Number of pages||45|
|Journal||Journal of the Association of Information Systems|
|State||Accepted/In press - 2019|