Known or knowing publics? Social media data mining and the question of public agency - Helen Kennedy; Giles Moss (Big Data & Society, 2015)
New methods to analyse social media data provide a powerful way to know publics and capture what they say and do. At the same time, access to these methods is uneven, with corporations and governments tending to have best access to relevant data and analytics tools. Critics raise a number of concerns about the implications dominant uses of data mining and analytics may have for the public: they result in less privacy, more surveillance and social discrimination, and they provide new ways of controlling how publics come to be represented and so understood. In this paper, we consider if a different relationship between the public and data mining might be established, one in which publics might be said to have greater agency and reflexivity vis-à-vis data power. Drawing on growing calls for alternative data regimes and practices, we argue that to enable this different relationship, data mining and analytics need to be democratised in three ways: they should be subject to greater public supervision and regulation, available and accessible to all, and used to create not simply known but reflexive, active and knowing publics. We therefore imagine conditions in which data mining is not just used as a way to know publics, but can become a means for publics to know themselves.