Abstract
As social media data mining becomes more and more ordinary, as we post, our posts get mined and this process gets repeated, new data relations emerge. These new data relations are characterised by a widespread desire for numbers. To talk about a desire for numbers, rather than a trust in numbers (Porter 1995), makes it possible to account for some of the contradictions that accompany the becoming-ordinary of social media data, such as hunger for and evangelism about but also frustration in and criticism of data and data mining. This widespread desire for numbers brings with it some troubling consequences: it becomes increasingly difficult to discuss problems with social media data mining despite recognition of them amongst data miners, and it has effects of all kinds on work and workers. Despite these problems, and because of the ubiquity of data and data mining, the possibility of doing good with data (and with data mining) endures. Together, these and other contradictory tendencies – the persistence of some old concerns; the emergence of new ones; data power and challenges to it – constitute the new data relations that emerge when social media data are ordinary. In this presentation, I illustrate this argument by drawing on action research with public sector organisations, interviews with commercial social media insights companies and their clients, focus groups with social media users and other research.
BIO
Helen Kennedy is Professor of Digital Society at the University of Sheffield. She has recently been researching what happens when social media data mining becomes widespread – this research will be published as a monograph entitled Post, Mine, Repeat: social media data mining becomes ordinary (Palgrave Macmillan, 2016, was funded by an AHRC Fellowship). Current research includes Seeing Data (www.seeingdata.org), which explores how non-experts relate to data visualisations (funded by an AHRC Digital Transformation large grant). Previous research has traversed digital media landscapes, covering topics including: homepages, identity and representation; race, class, gender inequality; learning disability and web accessibility; and web design and other creative digital work. She is currently interested in critical approaches to big data and data visualisation, how to make data more accessible to ordinary citizens, and whether data matter to people.
