Approximating Betweenness-Centrality ranking
2 papers with code • 0 benchmarks • 0 datasets
Betweenness-centrality is a popular measure in network analysis that aims to describe the importance of nodes in a graph. It accounts for the fraction of shortest paths passing through that node and is a key measure in many applications including community detection and network dismantling.
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Most implemented papers
ABCDE: Approximating Betweenness-Centrality ranking with progressive-DropEdge
MartinXPN/abcde
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PeerJ Computer Science 2021
It accounts for the fraction of shortest paths passing through that node and is a key measure in many applications including community detection and network dismantling.
A novel measure to identify influential nodes: Return Random Walk Gravity Centrality
To validate the effectiveness of the proposed centrality measure, it is compared with classic measures, such as Degree, Closeness, Betweenness, PageRank, and other measures based on the gravity model, effective distance and community-aware approaches.
