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Modeling Transitivity in Complex Networks
[article]
2015
arXiv
pre-print
An important source of high clustering coefficient in real-world networks is transitivity. However, existing approaches for modeling transitivity suffer from at least one of the following problems: i) they produce graphs from a specific class like bipartite graphs, ii) they do not give an analytical argument for the high clustering coefficient of the model, and iii) their clustering coefficient is still significantly lower than real-world networks. In this paper, we propose a new model for
arXiv:1411.0958v5
fatcat:fxpl6cfluzgr3o54v52priyrca