A new betweenness centrality measure based on an algorithm for ranking the nodes of a network
Article
English
RESTRICTED
Agryzkov, Taras
;
Oliver, JoseLuis
;
Tortosa, Leandro
;
Vicent, Jose F.
(2014)
 Publisher: Elsevier

Related identifiers:
doi: 10.1016/j.amc.2014.07.026

Subject:
Street network algorithms  PageRank algorithms  Centrality measures  Betweenness  Randomwalk betweenness  Eigenvector centrality  Ciencia de la ComputaciĆ³n e Inteligencia Artificial
We propose and discuss a new centrality index for urban street patterns represented as networks in geographical space. This centrality measure, that we call rankingbetweenness centrality, combines the idea behind the randomwalk 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 randomwalk betweenness centrality. A detailed example of a real urban street network is discussed in order to understand the process to evaluate the rankingbetweenness centrality proposed, performing some comparisons with other classical centrality measures.
This work was partially supported by Generalitat Valenciana Grant GV2012111.