Microanalysis Of Online Data: The methodological development of “digital CA”

• We discuss the application of conversation analysis (CA) to online interaction.
• We compare ‘digitised’ to ‘natively digital’ methods for researching online data.
• We discuss which features of CA can be usefully applied to online data.
• We consider the kinds of research questions that a digitised CA might wish to address.
• We explore the possibilities for developing natively digital analytic techniques.

This paper introduces the work of the MOOD (Microanalysis Of Online Data) network, an interdisciplinary association of academic researchers exploring ways of conducting close qualitative analyses of online interaction. Despite the fact that much online interaction meets the criteria for ‘conversation’, conversation analysis (CA) has only recently begun to grow and flourish as a methodology for analysing the overwhelming quantity of material that in many cases sits in archive form, visible to millions, on the Internet. We discuss the development of methods that are inherently suited for subjecting online interaction to the kind of rigorous analysis that conversation analysts have applied to talk of all kinds for several decades. We go on to explore the fundamental challenges that online data pose for CA, the value of many CA techniques for online analysis, and the possibilities of developing bespoke modes of analysis that are crafted for use with specific forms of online data (e.g. ‘tweets’ on Twitter).