Communicability Graph and Community Structures in Complex Networks
arXiv:0905.4103 · doi:10.1016/j.amc.2009.04.024
Abstract
We use the concept of the network communicability (Phys. Rev. E 77 (2008) 036111) to define communities in a complex network. The communities are defined as the cliques of a communicability graph, which has the same set of nodes as the complex network and links determined by the communicability function. Then, the problem of finding the network communities is transformed to an all-clique problem of the communicability graph. We discuss the efficiency of this algorithm of community detection. In addition, we extend here the concept of the communicability to account for the strength of the interactions between the nodes by using the concept of inverse temperature of the network. Finally, we develop an algorithm to manage the different degrees of overlapping between the communities in a complex network. We then analyze the USA airport network, for which we successfully detect two big communities of the eastern airports and of the western/central airports as well as two bridging central communities. In striking contrast, a well-known algorithm groups all but two of the continental airports into one community.
36 pages, 5 figures, to appear in Applied Mathematics and Computation
References in corpus (12)
- The structure and function of complex networks
- Community structure in social and biological networks
- Fast algorithm for detecting community structure in networks
- Uncovering the overlapping community structure of complex networks in nature and society
- Finding community structure in networks using the eigenvectors of matrices
- Cooperative Game Theory Approaches for Network Partitioning
- Functional cartography of complex metabolic networks
- Comparing community structure identification
- Community detection in complex networks using Extremal Optimization
- Communicability in complex networks
- Detecting communities in large networks
- Communities in Networks
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