Big Data-Driven Health Surveillance

Analysis here explains how relevant research decisions and developments are translated into research projects. The author specifically demonstrates how the use of big data collected by tech corporations is practically realised as well as discursively presented by researchers. The focus is on research projects, which have utilised sources that are not traditionally seen as ‘biomedical data’. Analyses of specific cases and references to contemporary developments are a particular focus of emphasis. Three clusters of cases in which diverse values are involved are presented: 1) Tweeting about illness and risk behaviour; 2) data retrieval through advertising relations; and 3) data mashups. The first cluster examines how Twitter’s data has been utilised as indicators of health risk behaviour. The second cluster explores researchers’ attempts to access, for example, Facebook data via advertising and marketing services. The third cluster focuses on publicly available platforms developed by university researchers which draw on data collected by tech corporations notably Google. These are cases in which the analytic possibilities of big data have led to the emergence of ‘technosciences’, i.e. academic research fields which are substantially grounded in technological changes. The aim here is to emphasise the complexities and contradictions, the methodological as well institutional dilemmas, and factors of influence co-constructing current modes of big data research.