Ranking Spreaders in Complex Networks Based on the Most Influential Neighbors
Joint Authors
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-08-23
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Identifying influential spreaders in complex networks is crucial for containing virus spread, accelerating information diffusion, and promoting new products.
In this paper, inspired by the effect of leaders on social ties, we propose the most influential neighbors’ k-shell index that is the weighted sum of the products between k-core values of itself and the node with the maximum k-shell values.
We apply the classical Susceptible-Infected-Recovered (SIR) model to verify the performance of our method.
The experimental results on both real and artificial networks show that the proposed method can quantify the node influence more accurately than degree centrality, betweenness centrality, closeness centrality, and k-shell decomposition method.
American Psychological Association (APA)
Yi, Ze-Long& Wu, Xiaokun& Li, Fan. 2018. Ranking Spreaders in Complex Networks Based on the Most Influential Neighbors. Discrete Dynamics in Nature and Society،Vol. 2018, no. 2018, pp.1-6.
https://search.emarefa.net/detail/BIM-1152519
Modern Language Association (MLA)
Yi, Ze-Long…[et al.]. Ranking Spreaders in Complex Networks Based on the Most Influential Neighbors. Discrete Dynamics in Nature and Society No. 2018 (2018), pp.1-6.
https://search.emarefa.net/detail/BIM-1152519
American Medical Association (AMA)
Yi, Ze-Long& Wu, Xiaokun& Li, Fan. Ranking Spreaders in Complex Networks Based on the Most Influential Neighbors. Discrete Dynamics in Nature and Society. 2018. Vol. 2018, no. 2018, pp.1-6.
https://search.emarefa.net/detail/BIM-1152519
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1152519