Education, Science, Technology, Innovation and Life
Open Access
Sign In

A Node Centrality Evaluation Model for Weighted Social Networks

Download as PDF

DOI: 10.23977/jnas.2019.11001 | Downloads: 10 | Views: 3801


Peng Wang 1


1 School of Economics and Management, Dalian University, No.10, Xuefu Avenue, Economic & Technical Development Zone, Dalian, Liaoning, The People's Republic of China(PRC)

Corresponding Author

Peng Wang


In this paper, we apply Principal Component Centrality (PCC), a centrality measure for unweighted networks, to weighted social networks, and propose a weighted centrality measure based on tie strength matrix (TSM). Experiment results show that weighted PCC outperforms weighted EVC (EigenVector Centrality) in spreading effectiveness, robustness and tolerance, hence is feasible and effective in weighted social networks.


Centrality, Key nodes, Social networks, Weighted networks


Peng Wang, A Node Centrality Evaluation Model for Weighted Social Networks, Journal of Networking, Architecture and Storage (2019) Vol. 1: 1-4. DOI:


[1] Alain Billionnet (2017) How to Take into Account Uncertainty in Species Extinction Probabilities for Phylogenetic Conservation Prioritization, Environmental Modeling & Assessment, 6, 535-548
[2] Ling Jiang (2017) Generalized multiobjective robustness and relations to set-valued optimization, Applied Mathematics and Computation, 9, 599-608.
[3] Hong-Zhi Wei (2019) Robustness to uncertain optimization using scalarization techniques and relations to multiobjective optimization. Applicable Analysis, 1, 119-136.

Downloads: 10
Visits: 3801

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.