Paper Info
Title
Identification of highly susceptible individuals in complex networks.
Abstract
Identifying highly susceptible individuals in spreading processes is of great significance in controlling outbreaks. In this paper, we explore the susceptibility of people in susceptible-infectious-recovered (SIR) and rumor spreading dynamics. We first study the impact of community structure on people’s susceptibility. Although the community structure can reduce the number of infected people for same infection rate, it will not significantly affect nodes’ susceptibility. We find the susceptibility of individuals is sensitive to the choice of spreading dynamics. For SIR spreading, since the susceptibility is highly correlated to nodes’ influence, the topological indicator k-shell can better identify highly susceptible individuals, outperforming degree, betweenness centrality and PageRank. In contrast, in rumor spreading model, where nodes’ susceptibility and influence have no clear correlation, degree performs the best among considered topological measures. Our finding highlights the significance of both topological features and spreading mechanisms in identifying highly susceptible population.
Year
DOI
Venue
2015
10.1016/j.physa.2015.03.046
Physica A: Statistical Mechanics and its Applications
Keywords
Field
DocType
Epidemic spreading,Susceptibility,Complex networks
PageRank,Population,Community structure,Quantum mechanics,Rumor,Theoretical computer science,Betweenness centrality,Complex network,Infection rate,Mathematics
Journal
Volume
ISSN
Citations 
432
0378-4371
0
PageRank 
References 
Authors
0.34
11
5
Name
Order
Citations
PageRank
ShaoTing Tang1101.97
Xian Teng2242.66
Sen Pei320.71
Shu Yan400.34
Zhiming Zheng512816.80