Journal article

Iterative resource allocation for ranking spreaders in complex networks

  • Ren, Zhuo-Ming Research Center of Complex Systems Science, University of Shanghai for Science and Technology Shanghai, China - Department of Physics, University of Fribourg, Switzerland
  • Zeng, An Department of Physics, University of Fribourg, Switzerland - School of Systems Science, Beijing Normal University - Beijing, China
  • Chen, Duan-Bing Department of Physics, University of Fribourg, Switzerland - Web Sciences Center, University of Electronic Science and Technology of China - Chengdu, China
  • Liao, Hao Department of Physics, University of Fribourg, Switzerland
  • Liu, Jian-Guo Research Center of Complex Systems Science, University of Shanghai for Science and Technology Shanghai, China
Show more…
    01.05.2014
Published in:
  • EPL (Europhysics Letters). - 2014, vol. 106, no. 4, p. 48005
English Ranking the spreading influence of nodes in networks is a very important issue with wide applications in many different fields. Various topology-based centrality measures have been proposed to identify influential spreaders. However, the spreading influence of a node is usually not only determined by its own centrality but also largely influenced by the centrality of neighbors. To incorporate the centrality information of neighbors in ranking spreaders, we design an iterative resource allocation (IRA) process in which the resource of nodes distributes to their neighbors according to neighbors' centrality. After iterations, the resource amount on each node will be stable and the final resources of nodes are used to rank their spreading influence. The iterative process can be applied to many traditional centrality measures including degree, K-shell, closeness, and betweenness. The validation of our method is based on the susceptible-infected-recovered (SIR) spreading in four representative real datasets. The results show that the ranking accuracy of the traditional centrality measures is remarkably enhanced by IRA.
Faculty
Faculté des sciences
Department
Physique
Language
  • English
Classification
Physics
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/303787
Statistics

Document views: 3 File downloads:
  • zen_ira.pdf: 1