Name
Abstract | ||
|---|---|---|
Since some realistic networks are influenced not only by increment behavior but also by the tunable clustering mechanism with new nodes to be added to networks, it is interesting to characterize the model for those actual networks. In this paper, a weighted local-world model, which incorporates increment behavior and the tunable clustering mechanism, is proposed and its properties are investigated, such as degree distribution and clustering coefficient. Numerical simulations are fitted to the model and also display good right-skewed scale-free properties. Furthermore, the correlation of vertices in our model is studied which shows the assortative property. The epidemic spreading process by weighted transmission rate on the model shows that the tunable clustering behavior has a great impact on the epidemic dynamic. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1088/1742-5468/2010/11/P11009 | JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT |
Keywords | Field | DocType |
growth processes,clustering techniques | Transmission rate,Statistical physics,Mathematical optimization,Correlation clustering,Vertex (geometry),Quantum mechanics,Correlation,Degree distribution,Clustering coefficient,Cluster analysis,Mathematics | Journal |
Volume | Issue | ISSN |
abs/1202.0351 | 11 | 1742-5468 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yinghong Ma | 1 | 26 | 13.76 |
| Huijia Li | 2 | 0 | 0.68 |
| Xiao-Dong Zhang | 3 | 97 | 19.87 |