  This paper introduces the notion of co-modularity, to co-cluster observations
of bipartite networks into co-communities. The task of co-clustering is to
group together nodes of one type with nodes of another type, according to the
interactions that are the most similar. The novel measure of co-modularity is
introduced to assess the strength of co-communities, as well as to arrange the
representation of nodes and clusters for visualisation, and to define an
objective function for optimisation. We demonstrate the usefulness of our
proposed methodology on simulated data, and with examples from genomics and
consumer-product reviews.
