Paper Info
Title
High Degree Vertices and Spread of Infections in Spatially Modelled Social Networks.
Abstract
We examine how the behaviour of high degree vertices in a network affects whether an infection spreads through communities or jumps between them. We study two stochastic susceptible-infected-recovered (SIR) processes and represent our network with a spatial preferential attachment (SPA) network. In one of the two epidemic scenarios we adjust the contagiousness of high degree vertices so that they are less contagious. We show that, for this scenario, the infection travels through communities rather than jumps between them. We conjecture that this is not the case in the other scenario, when contagion is independent of the degree of the originating vertex. Our theoretical results and conjecture are supported by simulations.
Year
DOI
Venue
2017
10.1007/978-3-319-67810-8_5
ALGORITHMS AND MODELS FOR THE WEB GRAPH, WAW 2017
Keywords
Field
DocType
Spatial graph model,Preferential attachment,Infection in networks,Contact process
Discrete mathematics,Combinatorics,Social network,Vertex (geometry),Computer science,Conjecture,Preferential attachment
Conference
Volume
ISSN
Citations 
10519
0302-9743
0
PageRank 
References 
Authors
0.34
8
2
Name
Order
Citations
PageRank
Joshua Feldman100.34
Jeannette Janssen229532.23