Growing hypergraphs with preferential linking

A family of models of growing hypergraphs with preferential rules of new linking is introduced and studied. The model hypergraphs evolve via the hyperedge-based growth as well as the node-based one, thus generalizing the preferential attachment models of scale-free networks. We obtain the degree dis...

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Bibliographic Details
Published in:Journal of the Korean Physical Society 2023, 83(9), , pp.713-722
Main Authors: Roh, Dahae, Goh, K. -I.
Format: Article
Language:English
Subjects:
Graph theory
Mathematical and Computational Physics
Mathematical models
Nodes
Original Paper - Cross-Disciplinary Physics and Related Areas of Science and Technology
Particle and Nuclear Physics
Physics
Physics and Astronomy
Power law
Size distribution
Theoretical
물리학
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Summary:A family of models of growing hypergraphs with preferential rules of new linking is introduced and studied. The model hypergraphs evolve via the hyperedge-based growth as well as the node-based one, thus generalizing the preferential attachment models of scale-free networks. We obtain the degree distribution and hyperedge size distribution for various combinations of node- and hyperedge-based growth modes. We find that the introduction of hyperedge-based growth can give rise to power law degree distribution P ( k ) ∼ k - γ even without node-wise preferential attachments. The hyperedge size distribution P ( s ) can take diverse functional forms, ranging from exponential to power law to a nonstationary one, depending on the specific hyperedge-based growth rule. Numerical simulations support the mean-field theoretical analytical predictions.
ISSN:0374-4884
1976-8524
DOI:10.1007/s40042-023-00909-4