首页|A Random Growth Model with Any Real or Theoretical Degree Distribution
A Random Growth Model with Any Real or Theoretical Degree Distribution
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NETL
The degree distributions of complex networks are usually considered to be power law。 However， it is not the case for a large number of them。 We thus propose a new model able to build random growing networks with (almost) any wanted degree distribution。 The degree distribution can either be theoretical or extracted from a real-world network。 The main idea is to invert the recurrence equation commonly used to compute the degree distribution in order to find a convenient attachment function for node connections - commonly chosen as linear。 We compute this attachment function for some classical distributions， as the power-law， broken power-law， geometric and Poisson distributions。 We also use the model on an undirected version of the Twitter network， for which the degree distribution has an unusual shape。
NETL
