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How to Identify the Most Powerful Node in Complex Networks? A Novel Entropy Centrality Approach

by 1, 1,2,* and 1
1
School of Economics and Management, Beihang University, Beijing 100191, China
2
Key Laboratory of Complex System Analysis and Management Decision, Ministry of Education, Beijing 100191, China
*
Author to whom correspondence should be addressed.
Entropy 2017, 19(11), 614; https://doi.org/10.3390/e19110614
Received: 9 October 2017 / Revised: 12 November 2017 / Accepted: 13 November 2017 / Published: 15 November 2017
(This article belongs to the Section Complexity)
Centrality is one of the most studied concepts in network analysis. Despite an abundance of methods for measuring centrality in social networks has been proposed, each approach exclusively characterizes limited parts of what it implies for an actor to be “vital” to the network. In this paper, a novel mechanism is proposed to quantitatively measure centrality using the re-defined entropy centrality model, which is based on decompositions of a graph into subgraphs and analysis on the entropy of neighbor nodes. By design, the re-defined entropy centrality which describes associations among node pairs and captures the process of influence propagation can be interpreted explained as a measure of actor potential for communication activity. We evaluate the efficiency of the proposed model by using four real-world datasets with varied sizes and densities and three artificial networks constructed by models including Barabasi-Albert, Erdos-Renyi and Watts-Stroggatz. The four datasets are Zachary’s karate club, USAir97, Collaboration network and Email network URV respectively. Extensive experimental results prove the effectiveness of the proposed method. View Full-Text
Keywords: complex network; social network; centrality; entropy centrality complex network; social network; centrality; entropy centrality
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MDPI and ACS Style

Qiao, T.; Shan, W.; Zhou, C. How to Identify the Most Powerful Node in Complex Networks? A Novel Entropy Centrality Approach. Entropy 2017, 19, 614. https://doi.org/10.3390/e19110614

AMA Style

Qiao T, Shan W, Zhou C. How to Identify the Most Powerful Node in Complex Networks? A Novel Entropy Centrality Approach. Entropy. 2017; 19(11):614. https://doi.org/10.3390/e19110614

Chicago/Turabian Style

Qiao, Tong, Wei Shan, and Chang Zhou. 2017. "How to Identify the Most Powerful Node in Complex Networks? A Novel Entropy Centrality Approach" Entropy 19, no. 11: 614. https://doi.org/10.3390/e19110614

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