Identifying Influential Nodes in Bipartite Networks Using the Clustering Coefficient
arXiv:1406.5814 · doi:10.1109/SITIS.2014.15
Abstract
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.