Modeling the Preference Memory in Social Networks

This paper proposes a new social network model - Preference Memory Network (PMN) to overcome the common deficiency that existing network models do not take into account the heterogeneity of nodes and the memory feature on node connections preference. Experimental results shows that Preference Memory Network model have small-world, scale-free, high clustering coefficient and short average shortest path. Moreover, the network model has a certain community structure with analysis on modularity, which reflects the characteristic of social network real-world situations.

[1]  Kazuhiro Takemoto,et al.  Evolving networks by merging cliques. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Hong-Bo Liu,et al.  Modeling the Complex Internet Topology: Modeling the Complex Internet Topology , 2009 .

[3]  Roger Guimerà,et al.  Modeling the world-wide airport network , 2004 .

[4]  Albert-László Barabási,et al.  Internet: Diameter of the World-Wide Web , 1999, Nature.

[5]  Guanrong Chen,et al.  Modelling of weighted evolving networks with community structures , 2006 .

[6]  Xiaofan Wang,et al.  Generalized local-world models for weighted networks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  Chunguang Li,et al.  An evolving network model with community structure , 2005, physics/0510239.

[8]  S. Redner How popular is your paper? An empirical study of the citation distribution , 1998, cond-mat/9804163.

[9]  Réka Albert,et al.  Structural vulnerability of the North American power grid. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.