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Evolution model for scientific collaboration network with local-world information 被引量:1

Evolution model for scientific collaboration network with local-world information
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摘要 In order to reveal the intrinsic properties of scientific collaboration networks, a new local-world evolution model on a scientific collaboration network is proposed by analysing the network growth mechanism. The act degree as the measurement of preferential attachment is taken, and the local-world information of nodes is taken into account. Analysis and simulation show that the node degree and the node strength obey the power-law distribution. Low average path length and high clustering coefficient are approved. Experiment indicates that the model can depict efficiently the topological structure and statistical characteristics of real-life scientific collaboration networks. In order to reveal the intrinsic properties of scientific collaboration networks, a new local-world evolution model on a scientific collaboration network is proposed by analysing the network growth mechanism. The act degree as the measurement of preferential attachment is taken, and the local-world information of nodes is taken into account. Analysis and simulation show that the node degree and the node strength obey the power-law distribution. Low average path length and high clustering coefficient are approved. Experiment indicates that the model can depict efficiently the topological structure and statistical characteristics of real-life scientific collaboration networks.
出处 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2014年第2期15-20,31,共7页 中国邮电高校学报(英文版)
基金 supported by the National Basic Research Program of China(2013CB329102) the National Natural Science Foundation of China(61372120,61271019,61101119,61121001,61072057,60902051) the PCSIRT(IRT1049) the Beijing Higher Education Young Elite Teacher Project(YETP0473)
关键词 scientific collaboration network evolution model local-world information scale-flee act degree scientific collaboration network, evolution model, local-world information, scale-flee, act degree
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