Growing hypergraphs with preferential linking

Dahae Roh, K. I. Goh

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)713-722
Number of pages10
JournalJournal of the Korean Physical Society
Volume83
Issue number9
DOIs
Publication statusPublished - 2023 Nov

Bibliographical note

Publisher Copyright:
© 2023, The Korean Physical Society.

Keywords

  • Growing hypergraph
  • Hypergraph
  • Power law distribution
  • Preferential linking

ASJC Scopus subject areas

  • General Physics and Astronomy

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