期刊
JOURNAL OF INFORMETRICS
卷 10, 期 1, 页码 299-311出版社
ELSEVIER
DOI: 10.1016/j.joi.2016.02.001
关键词
Coauthorship network; Modelling; Geometric graph; Hypergraph
资金
- Key Laboratory of High Performance Computing [201403-01]
- National University of Defense Technology Graduate Teaching Reform Project [201406-01]
Modeling coauthorship networks helps to understand the emergence and propagation of thoughts in academic society. A random geometric graph is proposed to model coauthor ship networks, the connection mechanism of which expresses the effects of the academic influences and homophily of authors, and the collaborations between research teams. Our analysis reveals that the modeled networks have a range of features of empirical coauthor ship networks, namely, the degree distribution made up of a mixture Poisson distribution with a power-law tail, clear community structure, small-world, high clustering, and degree assortativity. Moreover, the underlying formulae of the tail and forepart of the degree distribution, and the tail of the scaling relation between local clustering coefficient and degree are derived for the modeled networks, and are also applicable to the empirical networks. (C) 2016 Elsevier Ltd. All rights reserved.
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