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Stochastic Systems
Investigation of triangle counts in graphs evolving by clustering attachment
M. Vaičiulisa, N. M. Markovichb a Vilnius University
b V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow
Abstract:
The clustering attachment (CA) model proposed by Bagrow and Brockmann in 2013 may be used as an evolution tool for undirected random networks. A general definition of the CA model is introduced. Theoretical results are obtained for a new CA model that can be treated as the former’s limit in the case of the model parameters $\alpha\to0$ and $\epsilon = 0$. This study is focused on the triangle count of connected nodes at an evolution step $n$, an important characteristic of the network clustering considered in the literature. As is proved for the new model below, the total triangle count $\Delta n$ tends to infinity almost surely as $n\to\infty$ and the growth rate of $E\Delta_n$ at an evolution step $n\geqslant2$ is higher than the logarithmic one. Computer simulation is used to model sequences of triangle counts. The simulation is based on the generalized Pólya–Eggenberger urn model, a novel approach introduced here for the first time.
Keywords:
clustering attachment, clustering coefficient, node weight, random graph, evolution, urn model.
Citation:
M. Vaičiulis, N. M. Markovich, “Investigation of triangle counts in graphs evolving by clustering attachment”, Avtomat. i Telemekh., 2024, no. 11, 56–72; Autom. Remote Control, 85:11 (2024), 978–989
Linking options:
https://www.mathnet.ru/eng/at16471 https://www.mathnet.ru/eng/at/y2024/i11/p56
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