Sergey Melnik, Mason A. Porter, Peter J. Mucha, James P. Gleeson
We develop a new ensemble of modular random graphs in which degree-degree correlations can be different in each module. We present an analytical approach that allows one to analyze several types of binary dynamics operating on such networks, and we illustrate our approach using bond percolation, site percolation, and the Watts threshold model. The new network ensemble generalizes existing models by allowing a heterogeneous distribution of degree-degree correlations across modules, which is important for the consideration of nonidentical interacting networks.
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http://arxiv.org/abs/1207.1809
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