  We propose a novel measure to assess the presence of meso-scale structures in
complex networks. This measure is based on the identification of regular
patterns in the adjacency matrix of the network, and on the calculation of the
quantity of information lost when pairs of nodes are iteratively merged. We
show how this measure is able to quantify several meso-scale structures, like
the presence of modularity, bipartite and core-periphery configurations, or
motifs. Results corresponding to a large set of real networks are used to
validate its ability to detect non-trivial topological patterns.
