Rethinking empirical social sciences

Abstract

I consider some arguments of social science and humanities researchers about the challenge that big data presents for social science methods. What they suggest is that social scientists need to engage with big data rather than retreat into internal debates about its meaning and implications. Instead, understanding big data requires and provides an opportunity for the interdisciplinary development of methods that innovatively, critically and reflexively engage with new forms of data. Unlike data and methods that social scientists have typically worked with in the past, big data calls for skills and approaches that cut across disciplines. Drawing on work in science and technology studies and understandings of the ‘the social life of methods’, I argue that this is in part due to the fragmentation and redistribution of expertise, knowledge and methods that new data sources engender, including their incipient relations to government and industry and entanglements with social worlds.