An Analysis of Big Data on Health: Critique is Not Optional

The ‘social’ has always been a commercial and scientific resource – now in the digital age the competition regarding claims to which disciplines have justified understandings of this domain have intensified. The social sciences need to defend their subject area in order to preserve it. An application of the netnographic approach (Kozinets, 2010), social network analysis, data mining and machine-learning tools to highlight the certainties and uncertainties of Big Data and the Health Industry in order to start the process of uncovering the social and cultural forces that they are appropriating. What follows is the application of the tools of Big Data analytics on those that conduct Big Data analytics. There are competing discourses surrounding ‘Big Data’ and Health. On the one hand business, marketing and advertising interests are promoting Big Data as information that no longer requires theory or the scientific methodologies of old. On the other are voices from the academy; digital humanities and computational social sciences that wish to benefit from the volumes of available data. It is these (and other) competing discourses that are the target of this research. This paper argues that those engaged in ‘data without theory’ are generating a relational social mechanism similar to that of self-fulfilling prophesies of Merton, the network effects of Coleman and the bandwagon effects of Granovetter (Donati, 2015:66) and leaving no room for critique.

• https://snacda.com/2016/05/24/an-analysi...