Iterated Global Models for Complex Networks

Bonato, Anthony; Meger, Erin

doi:10.1007/978-3-030-48478-1_10

Cited by 5 publications

(1 citation statement)

References 11 publications

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“…Both the ILT and ILAT models were unified in the recent context of Iterated Local Models in [7]. Versions of the ILT model were considered for directed graphs [8] and hypergaphs [3], and a global version was considered in [11].…”

Section: Introductionmentioning

confidence: 99%

Iterative models for complex networks formed by extending cliques

Bonato¹,

Cushman²,

Marbach³

et al. 2022

Preprint

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We consider a new model for complex networks whose underlying mechanism is extending dense subgraphs. In the frustum model, we iteratively extend cliques over discrete-time steps. For many choices of the underlying parameters, graphs generated by the model densify over time. In the special case of the cone model, generated graphs provably satisfy properties observed in real-world complex networks such as the small world property and bad spectral expansion. We finish with a set of open problems and next steps for the frustum model.

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Section: Introductionmentioning

confidence: 99%

Iterative models for complex networks formed by extending cliques

Bonato¹,

Cushman²,

Marbach³

et al. 2022

Preprint

Self Cite

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An Evolving Network Model from Clique Extension

Bonato

Cushman

Marbach

et al. 2022

Lecture Notes in Computer Science

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Counts of small subgraphs, or graphlet counts, are widely applicable to measure graph similarity. Computing graphlet counts can be computationally expensive and may pose obstacles in network analysis. We study the role of cliques in graphlet counts as a method for graph similarity in social networks. Higher-order clustering coefficients and the Pivoter algorithm for exact clique counts are employed.

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