Digital platforms are not just software-based media, they are governing systems that control, interact, and accumulate. They also solidify markets; that is, social networks of exchange that do not necessarily leave data traces, into infrastructure, that is, material arrangements of traceable activity. This article examines the forms of domination found in this digital platform model, and corrects some existing simplistic theoretical conclusions about digital platforms. It first provides a schematic overview of digital infrastructures of governance, and the attendant systemic mechanics they engender. It then argues that we need a more syncretic, interdisciplinary approach to the platform-based economy. The shifting emphases of different academic disciplines in relation to digital platforms are only partially grounded in their different normative biases; they can also be attributed to use of different disciplinary lenses. The field of information systems management and design studies is chiefly concerned with direct, technical interplatform affordances and connections, and with providing observations of certain systemic attributes of digital platforms. Critical political economy, by contrast, mainly considers the emerging transnational, geopolitical formations of platform capitalism. The interplay between these different systemic mechanics is summarized and presented here in the concept of "platform logic."

The article proposes that social media platforms enable large volumes of user-driven circulation of media content, and argues for a combination of qualitative and quantitative considerations when analysing data from such platforms. Issues of context are vital; context must be understood both qualitatively (cultural setting) and quantitatively (statistical reference points for comparison). The authors emphasise that the possibilities of ‘big data’ should not tilt analyses so that sensitivities to subtler meanings are lost. By examining a recent research project of our own, examples are given of how topological network analysis can be successfully combined with close readings of strategically selected parts of the data and how, by doing so, context shifts can be identified that increase the reliability of the analysis. Consequently, it is recommended that mere number crunching is not enough, and that questions of ‘how,’ ‘why,’ and ‘whether’ are required in order to understand the phenomena in their societal settings.