Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2005-01-27
Physics
Condensed Matter
Disordered Systems and Neural Networks
22 pages, 10 figures, an error in Fig(7) is corrected
Scientific paper
Inspired by scientific collaboration networks, especially our empirical analysis of the network of econophysicists, an evolutionary model for weighted networks is proposed. Both degree-driven and weight-driven models are considered. Compared with the BA model and other evolving models with preferential attachment, there are two significant generalizations. First, besides the new vertex added in at every time step, old vertices can also attempt to build up new links, or to reconnect the existing links. The reconnection between both new-old and old-old nodes are recorded and the connecting times on every link is converted into the weight of the link. This provides a natural way for the evolution of edge weight. Second, besides degree and the weight of vertices, a path-related local information is also used as a reference in the preferential attachment. The path-related preferential attachment mechanism significantly increases the clustering coefficient of the network. The model shows the scale-free phenomena in degree and weight distribution. It also gives well qualitatively consistent behavior with the empirical results.
Di Zengru
Fan Ying
Li Menghui
Wang Dahui
Wu Jinshan
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