Betweenness is a measure of the centrality of a node in a network, and is normally calculated as the fraction of shortest paths between node pairs that pass through the node of interest. Betweenness is, in some sense, a measure of the influence a node has over the spread of information through the network. By counting only shortest paths, however, the conventional definition implicitly assumes that information spreads only along those shortest paths. Here, we propose a betweenness measure that relaxes this assumption, including contributions from essentially all paths between nodes, not just the shortest, although it still gives more weight to short paths. The measure is based on random walks, counting how often a node is traversed by a ran...
Abstract—Random geometric networks are mathematical structures consisting of a set of nodes placed r...
WOS: 000461317600020Centrality is a commonly used measure in network analysis to rank the relative i...
International audienceWe show that prominent centrality measures in network analysis are all based o...
VK: Saramäki, J.; TritonThis paper introduces two new closely related betweenness centrality measure...
Many scholars have tried to address the identification of critical nodes in complex networks from di...
Abstract. Betweenness is a centrality measure based on shortest paths, widely used in complex networ...
Estimating the importance or centrality of the nodes in large networks has recently attracted increa...
Betweenness measures provide quantitative tools to pick out fine details from the massive amount of ...
Betweenness is a good measure of the centrality of a vertex in a graph modeling social or communicat...
International audienceTypical betweenness centrality metrics neglect thepotential contribution of no...
Abstract. In our paper we compare two centrality measures of networks, between-ness and Linerank. Be...
Betweenness measures provide quantitative tools to pick out fine details from the massive amount of ...
In network analysis, it is useful to identify important vertices in a network. Based on the varying ...
Betweenness centrality based on shortest paths is a standard measure of control utilized in numerous...
We propose and discuss a new centrality index for urban street patterns represented as networks in g...
Abstract—Random geometric networks are mathematical structures consisting of a set of nodes placed r...
WOS: 000461317600020Centrality is a commonly used measure in network analysis to rank the relative i...
International audienceWe show that prominent centrality measures in network analysis are all based o...
VK: Saramäki, J.; TritonThis paper introduces two new closely related betweenness centrality measure...
Many scholars have tried to address the identification of critical nodes in complex networks from di...
Abstract. Betweenness is a centrality measure based on shortest paths, widely used in complex networ...
Estimating the importance or centrality of the nodes in large networks has recently attracted increa...
Betweenness measures provide quantitative tools to pick out fine details from the massive amount of ...
Betweenness is a good measure of the centrality of a vertex in a graph modeling social or communicat...
International audienceTypical betweenness centrality metrics neglect thepotential contribution of no...
Abstract. In our paper we compare two centrality measures of networks, between-ness and Linerank. Be...
Betweenness measures provide quantitative tools to pick out fine details from the massive amount of ...
In network analysis, it is useful to identify important vertices in a network. Based on the varying ...
Betweenness centrality based on shortest paths is a standard measure of control utilized in numerous...
We propose and discuss a new centrality index for urban street patterns represented as networks in g...
Abstract—Random geometric networks are mathematical structures consisting of a set of nodes placed r...
WOS: 000461317600020Centrality is a commonly used measure in network analysis to rank the relative i...
International audienceWe show that prominent centrality measures in network analysis are all based o...