The closeness and the betweenness centralities are two well known measures of importance of a vertex within a given complex network. Having high closeness or betweenness centrality can have positive impact on the vertex itself: hence, in this paper we consider the problem of determining how much a vertex can increase its centrality by creating a limited amount of new edges incident to it. We first prove that this problem does not admit a polynomial-time approximation scheme (unless P = NP), and we then propose a simple greedy approximation algorithm (with an almost tight approximation ratio), whose performance is then tested on synthetic graphs and real-world networks.

Greedily improving our own centrality in a network / Crescenzi, Pierluigi; D’Angelo, Gianlorenzo; Severini, Lorenzo; Velaj, Yllka. - STAMPA. - 9125:(2015), pp. 43-55. (Intervento presentato al convegno 14th International Symposium on Experimental Algorithms, SEA 2015 nel 2015) [10.1007/978-3-319-20086-6_4].

Greedily improving our own centrality in a network

CRESCENZI, PIERLUIGI;
2015

Abstract

The closeness and the betweenness centralities are two well known measures of importance of a vertex within a given complex network. Having high closeness or betweenness centrality can have positive impact on the vertex itself: hence, in this paper we consider the problem of determining how much a vertex can increase its centrality by creating a limited amount of new edges incident to it. We first prove that this problem does not admit a polynomial-time approximation scheme (unless P = NP), and we then propose a simple greedy approximation algorithm (with an almost tight approximation ratio), whose performance is then tested on synthetic graphs and real-world networks.
2015
Lecture Notes in Computer Science
14th International Symposium on Experimental Algorithms, SEA 2015
2015
Crescenzi, Pierluigi; D’Angelo, Gianlorenzo; Severini, Lorenzo; Velaj, Yllka
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1051077
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