The Crowd in the Cloud? Three challenges for gauging public opinion online

Much excitement surrounds the use of social sources of big data – harvested from popular networking platforms like Twitter and Facebook, as well as other forms of socially generated data including Wikipedia edits and Google searches – in the pursuit of social scientific discovery. In this paper I assess the extent to which these newly available sources of socially-generated big data can tell us about public opinion in a society at large. I draw on data from a series of interviews conducted with researchers at the forefront of big data approaches to social science, in order to outline the opportunities and issues around this area of research. In my analysis I identify three challenges to the validity of online public opinion measurement – the reliability of the data collected, the representativeness of the ‘sample’ being analysed, and the replicability of this form of public opinion research – and suggest various ways in which these challenges can be met.