Node Weight Distribution and Disparity of Some Collaboration-Competition Networks

We present an empirical investigation of 14 real world networks, which can be described by bipartite graphs. We show that the basic elements (the actor nodes) in all the networks cooperate and compete in some acts (activities, organizations, or events). Each node is assigned by a 'node weight', which denotes the obtained competition result. We are interested in the distribution and disparity of the node weight and propose three parameters for the description. Firstly, empirically we observe that the total node weight distributions of all the systems may be fitted by the so-called 'shifted power law' function form. The key parameters of the function, α and γ, can be used to describe the disparity. Secondly, a 'node weight disparity', Y, is defined for the same purpose. The empirical relationships among the parameters Y, α and γ, are obtained. From the relationships between Y and α as well as Y and γ, one can deduce the relationship between a and γ, which is in a good agreement with the empirically obtained relationship. The results show that the node weight distribution is very uneven.

[1]  Xuan Qi,et al.  Does the Compelled Cooperation Determine the Structure of a Complex Network , 2008 .

[2]  Xiaofan Wang,et al.  Unified index to quantifying heterogeneity of complex networks , 2008 .

[3]  M. Newman,et al.  Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Enrico Scalas,et al.  Fitting the empirical distribution of intertrade durations , 2008 .

[5]  Bei-Bei Su,et al.  A game theory model of urban public traffic networks , 2007 .

[6]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[7]  J. Szwabiński,et al.  Effects of random habitat destruction in a predator–prey model , 2006 .

[8]  Bei-Bei Su,et al.  Assortativity and act degree distribution of some collaboration networks , 2007 .

[9]  Da-Ren He,et al.  A kind of collaboration–competition networks , 2008 .

[10]  Zhi-Qiang Jiang,et al.  Scaling in the distribution of intertrade durations of Chinese stocks , 2008, 0804.3431.

[11]  A. Barabasi,et al.  Evolution of the social network of scientific collaborations , 2001, cond-mat/0104162.

[12]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994 .

[13]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[14]  John Scott What is social network analysis , 2010 .

[15]  Bernard Derrida,et al.  Statistical properties of randomly broken objects and of multivalley structures in disordered systems , 1987 .

[16]  M E Newman,et al.  Scientific collaboration networks. I. Network construction and fundamental results. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.