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A Node Centrality Evaluation Model for Weighted Social Networks

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DOI: 10.23977/jnas.2019.11001 | Downloads: 1 | Views: 49

Author(s)

Peng Wang 1

Affiliation(s)

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

ABSTRACT

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.

KEYWORDS

Centrality, Key nodes, Social networks, Weighted networks

CITE THIS PAPER

Peng Wang, A Node Centrality Evaluation Model for Weighted Social Networks, Journal of Networking, Architecture and Storage (2019) Vol. 1: 1-4. DOI: http://dx.doi.org/10.23977/jnas.2019.11001.

REFERENCES

[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.

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