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Title: Classes of preferential attachment and triangle preferential attachment models with power-law spectra
Abstract Preferential attachment (PA) models are a common class of graph models which have been used to explain why power-law distributions appear in the degree sequences of real network data. Among other properties of real-world networks, they commonly have non-trivial clustering coefficients due to an abundance of triangles as well as power laws in the eigenvalue spectra. Although there are triangle PA models and eigenvalue power laws in specific PA constructions, there are no results that existing constructions have both. In this article, we present a specific Triangle Generalized Preferential Attachment Model that, by construction, has non-trivial clustering. We further prove that this model has a power law in both the degree distribution and eigenvalue spectra.  more » « less
Award ID(s):
1909528
NSF-PAR ID:
10285909
Author(s) / Creator(s):
;
Editor(s):
Estrada, Ernesto
Date Published:
Journal Name:
Journal of Complex Networks
Volume:
8
Issue:
4
ISSN:
2051-1329
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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