The identification of influential nodes in complex network can be very
challenging. If the network has a community structure, centrality measures may
fail to identify the complete set of influential nodes, as the hubs and other
central nodes of the network may lie inside only one community. Here we define
a bipartite clustering coefficient that, by taking differently structured
clusters into account, can find important nodes across communities
