Nonlinear growth in weighted networks with neighborhood preferential attachment
2012 (English)In: Physica A: Statistical Mechanics and its Applications, ISSN 0378-4371, E-ISSN 1873-2119, Vol. 391, no 20, 4790-4797 p.Article in journal (Refereed) Published
We propose a nonlinear growing model for weighted networks with two significant characteristics: (i) the new weights triggered by new edges at each time step grow nonlinearly with time; and (ii) a neighborhood local-world exists for local preferential attachment, which is defined as one selected node and its neighbors. Global strength-driven and local weight-driven preferential attachment mechanisms are involved in our model. We study the evolution process through both mathematical analysis and numerical simulation, and find that the model exhibits a wide-range power-law distribution for node degree, strength, and weight. In particular, a nonlinear degree-strength relationship is obtained. This nonlinearity implies that accelerating growth of new weights plays a nontrivial role compared with accelerating growth of edges. Because of the specific local-world model, a small-world property emerges, and a significant hierarchical organization, independent of the parameters, is observed.
Place, publisher, year, edition, pages
2012. Vol. 391, no 20, 4790-4797 p.
Hierarchy, Local world, Nonlinear growth, Weighted evolving networks
Other Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-95064DOI: 10.1016/j.physa.2012.05.055ISI: 000306825300026ScopusID: 2-s2.0-84863476750OAI: oai:DiVA.org:kth-95064DiVA: diva2:526482
QC 201208072012-05-122012-05-122013-05-14Bibliographically approved