Ties often have a strength naturally associated with them that differentiate them from each other. Tie strength has been operationalized as weights. A few network measures have been proposed for weighted networks, including three common measures of node centrality: degree, closeness, and betweenness. However, these generalizations have solely focused on tie weights, and not on the number of ties, which was the central component of the original measures. This paper proposes generalizations that combine both these aspects. We illustrate the benefits of this approach by applying one of them to Freeman's EIES dataset. © 2010 Elsevier B.V
Studies in Computational Intelligence, Vol 424 entitled: Complex NetworksTechnical Session 1: Networ...
Abstract Existing centrality measures for social network analysis suggest the im-portance of an acto...
In this paper, we seek to find a computationally light centrality metric that could serve as an alte...
Ties often have a strength naturally associated with them that differentiate them from each other. T...
An important problem in network analysis is understanding how much nodes are important in order to \...
International audienceWe show that prominent centrality measures in network analysis are all based o...
Links play a significant role in the functioning of a complex network. The aim of this thesis is to ...
Within network analysis, various measures of node centrality have been developed. In this paper, for...
The analysis of network’s centralities has a high-level significance for many real-world applicatio...
International audienceTypical betweenness centrality metrics neglect thepotential contribution of no...
We propose a non-linear relationship between two of the most important measures of centrality in a n...
In the area of network analysis, centrality metrics play an important role in defining the “most imp...
The centrality of an edge in a graph is proposed to be the degree of sensitivity of a graph distance...
Abstract. In our paper we compare two centrality measures of networks, between-ness and Linerank. Be...
Centrality is widely used to measure which nodes are important in a network. In recent decades, nume...
Studies in Computational Intelligence, Vol 424 entitled: Complex NetworksTechnical Session 1: Networ...
Abstract Existing centrality measures for social network analysis suggest the im-portance of an acto...
In this paper, we seek to find a computationally light centrality metric that could serve as an alte...
Ties often have a strength naturally associated with them that differentiate them from each other. T...
An important problem in network analysis is understanding how much nodes are important in order to \...
International audienceWe show that prominent centrality measures in network analysis are all based o...
Links play a significant role in the functioning of a complex network. The aim of this thesis is to ...
Within network analysis, various measures of node centrality have been developed. In this paper, for...
The analysis of network’s centralities has a high-level significance for many real-world applicatio...
International audienceTypical betweenness centrality metrics neglect thepotential contribution of no...
We propose a non-linear relationship between two of the most important measures of centrality in a n...
In the area of network analysis, centrality metrics play an important role in defining the “most imp...
The centrality of an edge in a graph is proposed to be the degree of sensitivity of a graph distance...
Abstract. In our paper we compare two centrality measures of networks, between-ness and Linerank. Be...
Centrality is widely used to measure which nodes are important in a network. In recent decades, nume...
Studies in Computational Intelligence, Vol 424 entitled: Complex NetworksTechnical Session 1: Networ...
Abstract Existing centrality measures for social network analysis suggest the im-portance of an acto...
In this paper, we seek to find a computationally light centrality metric that could serve as an alte...