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The ongoing and intensifying datafication of our societies poses huge challenges as well as opportunities for social science to rethink core elements of its research enterprise. Prominently, there is a pressing need to move beyond the long-standing qualitative/quantitative divide. This paper is an argument towards developing a critical science of data, by bringing together the interpretive theoretical and ethical sensibilities of social science with the predictive and prognostic powers of data science and computational methods. I argue that the renegotiation of theories and research methods that must be made in order for them to be more relevant and useful, can be fruitfully understood through the metaphor of hacking social science: developing creative ways of exploiting existing tools in alternative and unexpected ways to solve problems

Hacking Social Science for the Age of Datafication