The datafication of our world offers huge challenges and opportunities for social science. The "data-drivenness" of computational research can occur at the expense of theoretical reflection and interpretation. Additionally, it can be difficult to reconcile the ‘quantitative’ dimensions of big data with the ‘qualitative’ sensibilities needed for its understanding. At the same time, this opens up possibilities for reimagining key principles of social enquiry.
In this experimental and provocative book, Simon Lindgren argues that a hybrid approach to data and theory must be developed in order to
make sense of today’s ambivalent, turbulent, and media-saturated political
landscape. He pushes for the development of a critical science of data,
joining the interpretive theoretical and ethical sensibilities of social
science with the predictive and prognostic powers of data science and
computational methods. In order for theories and research methods to
be more useful and relevant, they must be dismantled and put together in
new, alternative, and unexpected ways.
<i>Data Theory</i> is essential reading for social scientists and data scientists, as well as students taking courses in social theory and data, digital methods, big data, and data and society.