A Mutual Attraction Model for Both Assortative and Disassortative Weighted Networks

Details A Mutual Attraction Model for Both Assortative and Disassortative Weighted Networks A Mutual Attraction Model for Both Assortative and Disassortative Weighted Networks

2005-05-17

arxiv.org/abs/cond-mat/0505419v1

Physics

Condensed Matter

Disordered Systems and Neural Networks

4 pages, 3 figures

Scientific paper

10.1103/PhysRevE.73.016133

In most networks, the connection between a pair of nodes is the result of their mutual affinity and attachment. In this letter, we will propose a Mutual Attraction Model to characterize weighted evolving networks. By introducing the initial attractiveness $A$ and the general mechanism of mutual attraction (controlled by parameter $m$), the model can naturally reproduce scale-free distributions of degree, weight and strength, as found in many real systems. Simulation results are in consistent with theoretical predictions. Interestingly, we also obtain nontrivial clustering coefficient C and tunable degree assortativity r, depending on $m$ and A. Our weighted model appears as the first one that unifies the characterization of both assortative and disassortative weighted networks.

Affiliated with

Also associated with

No associations

Rating

A Mutual Attraction Model for Both Assortative and Disassortative Weighted Networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Mutual Attraction Model for Both Assortative and Disassortative Weighted Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Mutual Attraction Model for Both Assortative and Disassortative Weighted Networks will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-599642