Epidemic spreading on complex networks with community structures

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Abstract

Many real-world networks display a community structure. We study two random graph models that create a network with similar community structure as a given network. One model preserves the exact community structure of the original network, while the other model only preserves the set of communities and the vertex degrees. These models show that community structure is an important determinant of the behavior of percolation processes on networks, such as information diffusion or virus spreading: the community structure can both enforce as well as inhibit diffusion processes. Our models further show that it is the mesoscopic set of communities that matters. The exact internal structures of communities barely influence the behavior of percolation processes across networks. This insensitivity is likely due to the relative denseness of the communities.
Original languageEnglish
Article number29748
Number of pages7
JournalScientific Reports
Volume6
DOIs
Publication statusPublished - 2016

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@article{5d0ef9b9bfaf4c969088ff2e94a4938c,
title = "Epidemic spreading on complex networks with community structures",
abstract = "Many real-world networks display a community structure. We study two random graph models that create a network with similar community structure as a given network. One model preserves the exact community structure of the original network, while the other model only preserves the set of communities and the vertex degrees. These models show that community structure is an important determinant of the behavior of percolation processes on networks, such as information diffusion or virus spreading: the community structure can both enforce as well as inhibit diffusion processes. Our models further show that it is the mesoscopic set of communities that matters. The exact internal structures of communities barely influence the behavior of percolation processes across networks. This insensitivity is likely due to the relative denseness of the communities.",
author = "C. Stegehuis and {van der Hofstad}, R.W. and {van Leeuwaarden}, J.S.H.",
year = "2016",
doi = "10.1038/srep29748",
language = "English",
volume = "6",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",

}

Epidemic spreading on complex networks with community structures. / Stegehuis, C.; van der Hofstad, R.W.; van Leeuwaarden, J.S.H.

In: Scientific Reports, Vol. 6, 29748, 2016.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Epidemic spreading on complex networks with community structures

AU - Stegehuis, C.

AU - van der Hofstad, R.W.

AU - van Leeuwaarden, J.S.H.

PY - 2016

Y1 - 2016

N2 - Many real-world networks display a community structure. We study two random graph models that create a network with similar community structure as a given network. One model preserves the exact community structure of the original network, while the other model only preserves the set of communities and the vertex degrees. These models show that community structure is an important determinant of the behavior of percolation processes on networks, such as information diffusion or virus spreading: the community structure can both enforce as well as inhibit diffusion processes. Our models further show that it is the mesoscopic set of communities that matters. The exact internal structures of communities barely influence the behavior of percolation processes across networks. This insensitivity is likely due to the relative denseness of the communities.

AB - Many real-world networks display a community structure. We study two random graph models that create a network with similar community structure as a given network. One model preserves the exact community structure of the original network, while the other model only preserves the set of communities and the vertex degrees. These models show that community structure is an important determinant of the behavior of percolation processes on networks, such as information diffusion or virus spreading: the community structure can both enforce as well as inhibit diffusion processes. Our models further show that it is the mesoscopic set of communities that matters. The exact internal structures of communities barely influence the behavior of percolation processes across networks. This insensitivity is likely due to the relative denseness of the communities.

U2 - 10.1038/srep29748

DO - 10.1038/srep29748

M3 - Article

C2 - 27440176

VL - 6

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

M1 - 29748

ER -