The agglomeration phenomenon influence on the scaling law of the scientific collaboration system

Ai-Zhong Shen, Jin-Li Guo, Guo-Lin Wu and Shu-Wei Jia

Chaos, Solitons & Fractals, 2018, vol. 114, issue C, 461-467

Abstract: This paper presents a scientific collaboration hypernetwork evolution model with adjustable clustering coefficient in which the authors are regarded as nodes and the hyperedges are the cooperative articles. Firstly, we build the scientific cooperation hypernetwork through the real paper data which comes from the database of arxive. The empirical results show that the node's hyperdegree follows the power law distribution, but the hyperedge's node-degree has the exponent distribution. In addition, we establish the scientific collaboration clustering hypernetwork evolution model by employing the Poisson process theory and the continuous method for studying the agglomeration phenomenon of scientific cooperation system. The theoretical analysis shows that the node's hyperdegree distribution has scale-free characteristics. The power index of our model is independent of the clustering coefficient, and the theoretical analyses agree with the conducted numerical simulations. Moreover, our model not only describes the scale-free property, but also depicts the phenomenon of agglomeration. Both the properties are usually coexist in the scientific cooperation, our model is more actual.

Keywords: Scientific collaboration; Hypergraph; Hypernetwork; Scaling law; Clustering coefficient (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:114:y:2018:i:c:p:461-467

DOI: 10.1016/j.chaos.2018.07.037

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