Random intersection graphs with communities

Fuente: arXiv
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Autori principali: van der Hofstad, Remco, Komjathy, Julia, Vadon, Viktoria
Natura: Preprint
Pubblicazione: 2018
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_version_ 1866918286301593600
author van der Hofstad, Remco
Komjathy, Julia
Vadon, Viktoria
author_facet van der Hofstad, Remco
Komjathy, Julia
Vadon, Viktoria
contents Random intersection graphs model networks with communities, assuming an underlying bipartite structure of groups and individuals, where these groups may overlap. Group memberships are generated through the bipartite configuration model. Conditionally on the group memberships, the classical random intersection graph is obtained by connecting individuals when they are together in at least one group. We generalize this definition, allowing for arbitrary community structures within the groups. In our new model, groups might overlap and they have their own internal structure described by a graph, the classical setting corresponding to groups being complete graphs. Our model turns out to be tractable. We analyze the overlapping structure of the communities, derive the asymptotic degree distribution and the local clustering coefficient. These proofs rely on local weak convergence, which also implies that subgraph counts converge. We further exploit the connection to the bipartite configuration model, for which we also prove local weak convergence, and which is interesting in its own right.
format Preprint
id arxiv_https___arxiv_org_abs_1809_02514
institution arXiv
publishDate 2018
record_format arxiv
spellingShingle Random intersection graphs with communities
van der Hofstad, Remco
Komjathy, Julia
Vadon, Viktoria
Probability
Combinatorics
60C05, 05C80, 90B15
Random intersection graphs model networks with communities, assuming an underlying bipartite structure of groups and individuals, where these groups may overlap. Group memberships are generated through the bipartite configuration model. Conditionally on the group memberships, the classical random intersection graph is obtained by connecting individuals when they are together in at least one group. We generalize this definition, allowing for arbitrary community structures within the groups. In our new model, groups might overlap and they have their own internal structure described by a graph, the classical setting corresponding to groups being complete graphs. Our model turns out to be tractable. We analyze the overlapping structure of the communities, derive the asymptotic degree distribution and the local clustering coefficient. These proofs rely on local weak convergence, which also implies that subgraph counts converge. We further exploit the connection to the bipartite configuration model, for which we also prove local weak convergence, and which is interesting in its own right.
title Random intersection graphs with communities
topic Probability
Combinatorics
60C05, 05C80, 90B15
url https://arxiv.org/abs/1809.02514