A Generalized Configuration Model With Triadic Closure

In this paper we present a generalized configuration model with random triadic closure (GCTC). This possesses five fundamental properties: large clustering coefficient, power law degree distribution, short path length, non-zero Pearson correlation, and existence of community structures. We analytically derive the correlation coefficient proposed model. select few datasets real-world networks. By simulation, show that GCTC matches very well in terms correlations coefficients. also test three well-known detection algorithms on our model, other prevalent benchmark models. performs equally as Finally, perform influence diffusion using independent cascade linear threshold spreads are much closer to those than suggests is suitable tool study network science problems where or plays an important role.