Communities as Vague Operators: Epistemological Questions for a Critical Heuristics of Community Detection Algorithms

In this article, we aim to analyse the nature and epistemic consequences of what figures in network science as patterns of nodes and edges called 'communities'. Tracing these as multi-faceted and ambivalent, we propose to describe the concept of community as a 'vague operator' related to Susan Leigh Star's notion of the boundary object but more loose, like a collection of hints, and propose that the ability to construct different modes of faceting that are both vague and hyper-precise, in semiotic, technical and social terms is core both to digital politics and the analysis of 'communities'. Engaging with these formations in terms drawn from mathematics and software studies enables a wider mapping of their formation. Disentangling different lineages in network science then allows us to contextualise the founding account of 'community' popularised by Michelle Girvan and Mark Newman in 2002. After studying one particular community detection algorithm, the so called 'Louvain algorithm', we comment on controversies arising with some of their more ambiguous applications. We argue that 'community' can act as a real abstraction with the power to reshape social relations such as producing echo chambers in social networking sites. To rework the epistemological terms of community detection, we draw on debates and propositions in the literature of network science to imagine a 'critical heuristics' that embraces partiality, epistemic humbleness, reflexivity and artificiality.