  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 patterns as multi-faceted and ambivalent, we
propose to describe the concept of community as a 'vague operator', a variant
of Susan Leigh Star's notion of the boundary object, and propose that the
ability to construct different modes of description that are both vague in some
registers and hyper-precise in others, 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 widely-used '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 and propose a reconsideration
of vague operators, we draw on debates and propositions within the literature
of network science to imagine a 'critical heuristics' that embraces partiality,
epistemic humbleness, reflexivity and artificiality.
