Challenging social media analytics: web science perspectives

Abstract

In this paper we outline some of the challenges for social media analytics and -- at the same time - challenge existing approaches to social media analysis. Specifically, we suggest that there is an unhelpful gulf between social scientific approaches, which offer rich theoretical and methodological understandings of the social; and computational approaches which offer sophisticated methods for data harvesting, interrogation and modelling. Brought together these approaches might meet the challenges facing social media analytics and produce a different order of understanding. We offer two preliminary examples of this synthesis in practice: first, we show how established computational tools might be harnessed to address theoretically grounded empirical questions about the social; and second we consider social theories might inspire the development of new methodological tools for social media analytics. In doing so, we aim to contribute to the development of interdisciplinary social media analytics with in a broader framework of Web Science.