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Mathematical Problems in Engineering
Volume 2015, Article ID 675713, 8 pages
http://dx.doi.org/10.1155/2015/675713
Research Article

Identifying Super-Spreader Nodes in Complex Networks

1Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu 300, Taiwan
2Department of Computer Science and Information Engineering, School of Electrical and Computer Engineering, College of Engineering, Chang Gung University, 259 Wen Hwa 1st Road, Taoyuan 333, Taiwan

Received 26 May 2014; Accepted 25 September 2014

Academic Editor: He Huang

Copyright © 2015 Yu-Hsiang Fu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Identifying the most influential individuals spreading information or infectious diseases can assist or hinder information dissemination, product exposure, and contagious disease detection. Hub nodes, high betweenness nodes, high closeness nodes, and high -shell nodes have been identified as good initial spreaders, but efforts to use node diversity within network structures to measure spreading ability are few. Here we describe a two-step framework that combines global diversity and local features to identify the most influential network nodes. Results from susceptible-infected-recovered epidemic simulations indicate that our proposed method performs well and stably in single initial spreader scenarios associated with various complex network datasets.