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zbMATH Open
Article . 2018
Data sources: zbMATH Open
DBLP
Article . 2020
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Closeness centrality in some splitting networks.

Closeness centrality in some splitting networks
Authors: Aytac, Vecdi; Turaci, Tufan;

Closeness centrality in some splitting networks.

Abstract

A central issue in the analysis of complex networks is the assessment of their robustness and vulnerability. A variety of measures have been proposed in the literature to quantify the robustness of networks, and a number of graph-theoretic parameters have been used to derive formulas for calculating network reliability. Centrality parameters play an important role in the field of network analysis. Numerous studies have proposed and analyzed several centrality measures. We consider closeness centrality which is defined as the total graph-theoretic distance to all other vertices in the graph. In this paper, closeness centrality of some splitting graphs is calculated, and exact values are obtained.

WOS: 000449530100003

Countries
Moldova (Republic of), Turkey
Related Organizations
Keywords

Graph theory, closeness centrality, Electronic computers. Computer science, Graph theory (including graph drawing) in computer science, graph theory, Complex networks, QA75.5-76.95, complex networks, Small world graphs, complex networks (graph-theoretic aspects), splitting graphs., splitting graphs, network design and communication

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
gold