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Paper short abstract:

Social data science has not come to terms with socio-technical transformations of life in a digital age. To address this, we must make the situation the unit of analysis. But most situational approaches assume a "fieldsite." How do we move from situational analysis to situational analytics?

Paper long abstract:

It is argued that digital data and tools enable the reconciliation of foundational oppositions in social research, such as that between content and context. Analytic operations that were previously assumed to require field work are brought within the frame of data analysis, with the aid of computational methods like natural language processing (Nelson 2017). But it is becoming clear that data analytics throws up methodological problems of its own: what operations enable the specification of events, issues and actors? how do capacities for intervention emerge from this? This paper proposes that if the digital has transformed the status of 'the field', this is due to socio-technical transformations of the settings of everyday life as much as to the analytic prowess of data science. Digital architectures make latent aspects of social life re-portable and share-able, and this renders social life more artificial, less spontaneous, and thinly structured, giving rise to we call "semi-fields" (Kelly, 2012). How to attune our analysis to these transformations of the very composition of social life in the wake of the proliferation of digital devices? To conduct social inquiry by digital means, we must counteract social ontologies designed into digital architectures, by making the situation our unit of analysis. In this we follow pragmatist and performative approaches and in particular Adele Clarke (2005). However, most situational approaches still assume the "field": what elaborations are needed to apprehend situations as they unfold in semi-fields? How do we move from situational analysis to situational analytics?