A new betweenness centrality measure based on an algorithm for ranking the nodes of a network

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/44390
Información del item - Informació de l'item - Item information
Title: A new betweenness centrality measure based on an algorithm for ranking the nodes of a network
Authors: Agryzkov, Taras | Oliver, Jose-Luis | Tortosa, Leandro | Vicent, Jose F.
Research Group/s: Análisis y Visualización de Datos en Redes (ANVIDA)
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial
Keywords: Street network algorithms | PageRank algorithms | Centrality measures | Betweenness | Random-walk betweenness | Eigenvector centrality
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Issue Date: 1-Oct-2014
Publisher: Elsevier
Citation: Applied Mathematics and Computation. 2014, 244: 467-478. doi:10.1016/j.amc.2014.07.026
Abstract: We propose and discuss a new centrality index for urban street patterns represented as networks in geographical space. This centrality measure, that we call ranking-betweenness centrality, combines the idea behind the random-walk betweenness centrality measure and the idea of ranking the nodes of a network produced by an adapted PageRank algorithm. We initially use a PageRank algorithm in which we are able to transform some information of the network that we want to analyze into numerical values. Numerical values summarizing the information are associated to each of the nodes by means of a data matrix. After running the adapted PageRank algorithm, a ranking of the nodes is obtained, according to their importance in the network. This classification is the starting point for applying an algorithm based on the random-walk betweenness centrality. A detailed example of a real urban street network is discussed in order to understand the process to evaluate the ranking-betweenness centrality proposed, performing some comparisons with other classical centrality measures.
Sponsor: This work was partially supported by Generalitat Valenciana Grant GV2012-111.
URI: http://hdl.handle.net/10045/44390
ISSN: 0096-3003 (Print) | 1873-5649 (Online)
DOI: 10.1016/j.amc.2014.07.026
Language: eng
Type: info:eu-repo/semantics/article
Peer Review: si
Publisher version: http://dx.doi.org/10.1016/j.amc.2014.07.026
Appears in Collections:INV - ANVIDA - Artículos de Revistas

Files in This Item:
Files in This Item:
File Description SizeFormat 
Thumbnail2014_Agryzkov_etal_AMC_final.pdfVersión final (acceso restringido)1,7 MBAdobe PDFOpen    Request a copy


Items in RUA are protected by copyright, with all rights reserved, unless otherwise indicated.