Stochastic blockmodels and community structure in networks

  title={Stochastic blockmodels and community structure in networks},
  author={Brian Karrer and Mark E. J. Newman},
  journal={Physical review. E, Statistical, nonlinear, and soft matter physics},
  volume={83 1 Pt 2},
Stochastic blockmodels have been proposed as a tool for detecting community structure in networks as well as for generating synthetic networks for use as benchmarks. Most blockmodels, however, ignore variation in vertex degree, making them unsuitable for applications to real-world networks, which typically display broad degree distributions that can significantly affect the results. Here we demonstrate how the generalization of blockmodels to incorporate this missing element leads to an… CONTINUE READING
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