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A distributed hypergraph model for simulating the evolution of large coauthorship networks

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  • Zheng Xie

    (National University of Defense Technology)

Abstract

The coauthorship in a paper set can be expressed by a hypergraph, namely a system with heterogeneously multinary relationship. The coauthorship network of that paper set is the simple graph extracted from that hypergraph. We designed a distributed hypergraph model to simulate the dynamics of large coauthorship networks in a full-scale manner. Its assembly mechanism of hyperedges is driven by Lotka’s law and a cooperative game that maximizes a benefit-cost ratio for coauthoring a paper. The model is built on a circle to express the game, expressing the cost by the distance between nodes. The benefit of coauthoring with a productive author or one with many coauthors is expressed by the cumulative degree or hyperdegree of nodes. The model successfully simulates the multimodal features emerged in the evolutions of coauthorship patterns, the clustering of nodes, the degree assortativity of linked nodes, degree and hyperdegree distributions. This model has the potential to be a null model for studying the complexity of the large social networks arising from other specific collaboration behaviors.

Suggested Citation

  • Zheng Xie, 2021. "A distributed hypergraph model for simulating the evolution of large coauthorship networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4609-4638, June.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:6:d:10.1007_s11192-021-03991-2
    DOI: 10.1007/s11192-021-03991-2
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    Cited by:

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    2. Vincenza Carchiolo & Marco Grassia & Michele Malgeri & Giuseppe Mangioni, 2022. "Co-Authorship Networks Analysis to Discover Collaboration Patterns among Italian Researchers," Future Internet, MDPI, vol. 14(6), pages 1-15, June.

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