[EN] A general growth model of random networks based on centrality measures is introduced. This formalism extends the well-known models of preferential attachment. We propose to set the preferential attachment using a linear function of some centrality measures ranging from local to global scale. The aim is to include spectral measures, such as PageRank and Bonacich, and geodesic measures, such as betweenness and closeness. In this paper we present a first analysis using degree and Personalized PageRank.Supported by Spanish DGI grant MTM2010-18674 Supported by Spanish DGI grant MTM2009-13848Pedroche Sánchez, F.; Criado, R.; García, E.; Romance, M. (2011). Matrix growth models based on centrality measures: a first analysis. International Jo...
Abstract: We propose a new model of social network growth. This model bases on the followi...
We derive new, exact expressions for network centrality vectors associated with classical Watts–Stro...
Abstract. Many popular measures used in social network analysis, including centrality, are based on ...
[EN] A general growth model of random networks based on centrality measures is introduced. This form...
We consider a broad class of walk-based, parameterized node centrality measures for network analysis...
All measures of centrality in graphs seem to be correlated with degree, the sheer number of connecti...
We seek to identify one or more computationally light-weight centrality metrics that have a high cor...
In this paper, we seek to find a computationally light centrality metric that could serve as an alte...
We perform here a comparative study on the behaviour of real and synthetic social networks with resp...
We describe a complete theory for walk-based centrality indices in complex networks defined in terms...
none3noTwo concepts of centrality have been defined in complex networks. The first considers the cen...
In recent decades, a number of centrality metrics describing network properties of nodes have been p...
The role of an actor in a social network is identified through a set of measures called centrality. ...
Complex networks are characterized by heterogeneous distributions of the degree of nodes, which prod...
Centrality and influence spread are two of the most studied concepts in social network analysis. In ...
Abstract: We propose a new model of social network growth. This model bases on the followi...
We derive new, exact expressions for network centrality vectors associated with classical Watts–Stro...
Abstract. Many popular measures used in social network analysis, including centrality, are based on ...
[EN] A general growth model of random networks based on centrality measures is introduced. This form...
We consider a broad class of walk-based, parameterized node centrality measures for network analysis...
All measures of centrality in graphs seem to be correlated with degree, the sheer number of connecti...
We seek to identify one or more computationally light-weight centrality metrics that have a high cor...
In this paper, we seek to find a computationally light centrality metric that could serve as an alte...
We perform here a comparative study on the behaviour of real and synthetic social networks with resp...
We describe a complete theory for walk-based centrality indices in complex networks defined in terms...
none3noTwo concepts of centrality have been defined in complex networks. The first considers the cen...
In recent decades, a number of centrality metrics describing network properties of nodes have been p...
The role of an actor in a social network is identified through a set of measures called centrality. ...
Complex networks are characterized by heterogeneous distributions of the degree of nodes, which prod...
Centrality and influence spread are two of the most studied concepts in social network analysis. In ...
Abstract: We propose a new model of social network growth. This model bases on the followi...
We derive new, exact expressions for network centrality vectors associated with classical Watts–Stro...
Abstract. Many popular measures used in social network analysis, including centrality, are based on ...
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