International audienceA class of centrality measures called betweenness centralities reflects degree of participation of edges or nodes in communication between different parts of the network. The original shortest-path betweenness centrality is based on counting shortest paths which go through a node or an edge. One of shortcomings of the shortest-path betweenness centrality is that it ignores the paths that might be one or two hops longer than the shortest paths, while the edges on such paths can be important for communication processes in the network. To rectify this shortcoming a current flow betweenness centrality has been proposed. Similarly to the shortest-path betweenness, it has prohibitive complexity for large size networks. In th...
International audienceTypical betweenness centrality metrics neglect thepotential contribution of no...
Betweenness is a measure of the centrality of a node in a network, and is normally calculated as the...
Centrality indices are an important tool in network analysis, and many of them are derived from the ...
A class of centrality measures called betweenness centralities reflects degree of participation of e...
Abstract. A class of centrality measures called betweenness centralities reflects degree of particip...
—The computation of nodes centrality is of great importance for the analysis of graphs. The current...
International audienceBetweenness centrality is one of the basic concepts in the analysis of social ...
We consider variations of two well-known centrality measures, betweenness and closeness, witha diffe...
The current flow betweenness centrality is a useful tool to estimate traffic status in spatial netwo...
International audienceThe ability of a node to relay information in a network is often measured usin...
Quantitatively assessing the importance or criticality of each link in a network is of practical val...
Betweenness centrality quantifies the importance of a vertex for the information flow in a network. ...
AbstractThe betweenness is a well-known measure of centrality of a node in a network. We consider th...
VK: Saramäki, J.; TritonThis paper introduces two new closely related betweenness centrality measure...
AbstractBetweenness centrality is a graph analytic that states the importance of a vertex based on t...
International audienceTypical betweenness centrality metrics neglect thepotential contribution of no...
Betweenness is a measure of the centrality of a node in a network, and is normally calculated as the...
Centrality indices are an important tool in network analysis, and many of them are derived from the ...
A class of centrality measures called betweenness centralities reflects degree of participation of e...
Abstract. A class of centrality measures called betweenness centralities reflects degree of particip...
—The computation of nodes centrality is of great importance for the analysis of graphs. The current...
International audienceBetweenness centrality is one of the basic concepts in the analysis of social ...
We consider variations of two well-known centrality measures, betweenness and closeness, witha diffe...
The current flow betweenness centrality is a useful tool to estimate traffic status in spatial netwo...
International audienceThe ability of a node to relay information in a network is often measured usin...
Quantitatively assessing the importance or criticality of each link in a network is of practical val...
Betweenness centrality quantifies the importance of a vertex for the information flow in a network. ...
AbstractThe betweenness is a well-known measure of centrality of a node in a network. We consider th...
VK: Saramäki, J.; TritonThis paper introduces two new closely related betweenness centrality measure...
AbstractBetweenness centrality is a graph analytic that states the importance of a vertex based on t...
International audienceTypical betweenness centrality metrics neglect thepotential contribution of no...
Betweenness is a measure of the centrality of a node in a network, and is normally calculated as the...
Centrality indices are an important tool in network analysis, and many of them are derived from the ...