zhang-physarumpreader-2015.pdf (2.99 MB)
PhysarumSpreader: a new bio-Inspired methodology for identifying influential spreaders in complex networks
journal contribution
posted on 2015-12-18, 00:00 authored by H Wang, Y Zhang, Zili ZhangZili Zhang, S Mahadevan, Y DengIdentifying influential spreaders in networks, which contributes to optimizing the use of available resources and efficient spreading of information, is of great theoretical significance and practical value. A random-walk-based algorithm LeaderRank has been shown as an effective and efficient method in recognizing leaders in social network, which even outperforms the well-known PageRank method. As LeaderRank is initially developed for binary directed networks, further extensions should be studied in weighted networks. In this paper, a generalized algorithm PhysarumSpreader is proposed by combining LeaderRank with a positive feedback mechanism inspired from an amoeboid organism called Physarum Polycephalum. By taking edge weights into consideration and adding the positive feedback mechanism, PhysarumSpreader is applicable in both directed and undirected networks with weights. By taking two real networks for examples, the effectiveness of the proposed method is demonstrated by comparing with other standard centrality measures.
History
Journal
PloS oneVolume
10Issue
12Article number
e0145028Pagination
1 - 21Publisher
Public Library of ScienceLocation
San Francisco, Calif.Publisher DOI
ISSN
1932-6203eISSN
1932-6203Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2015, The AuthorsUsage metrics
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