Defined in File Centrality.hpp
public NetworKit::Algorithm (Class Algorithm)
public NetworKit::AlgebraicPageRank< Matrix > (Template Class AlgebraicPageRank)
public NetworKit::AlgebraicSpanningEdgeCentrality< Matrix > (Template Class AlgebraicSpanningEdgeCentrality)
public NetworKit::ApproxBetweenness (Class ApproxBetweenness)
public NetworKit::ApproxCloseness (Class ApproxCloseness)
public NetworKit::ApproxElectricalCloseness (Class ApproxElectricalCloseness)
public NetworKit::Betweenness (Class Betweenness)
public NetworKit::Closeness (Class Closeness)
public NetworKit::CoreDecomposition (Class CoreDecomposition)
public NetworKit::DegreeCentrality (Class DegreeCentrality)
public NetworKit::DynApproxBetweenness (Class DynApproxBetweenness)
public NetworKit::DynBetweenness (Class DynBetweenness)
public NetworKit::DynKatzCentrality (Class DynKatzCentrality)
public NetworKit::EigenvectorCentrality (Class EigenvectorCentrality)
public NetworKit::EstimateBetweenness (Class EstimateBetweenness)
public NetworKit::ForestCentrality (Class ForestCentrality)
public NetworKit::HarmonicCloseness (Class HarmonicCloseness)
public NetworKit::KPathCentrality (Class KPathCentrality)
public NetworKit::KatzCentrality (Class KatzCentrality)
public NetworKit::LaplacianCentrality (Class LaplacianCentrality)
public NetworKit::LocalClusteringCoefficient (Class LocalClusteringCoefficient)
public NetworKit::LocalPartitionCoverage (Class LocalPartitionCoverage)
public NetworKit::LocalSquareClusteringCoefficient (Class LocalSquareClusteringCoefficient)
public NetworKit::PageRank (Class PageRank)
public NetworKit::Sfigality (Class Sfigality)
public NetworKit::SpanningEdgeCentrality (Class SpanningEdgeCentrality)
Abstract base class for centrality measures.
Subclassed by NetworKit::AlgebraicPageRank< Matrix >, NetworKit::AlgebraicSpanningEdgeCentrality< Matrix >, NetworKit::ApproxBetweenness, NetworKit::ApproxCloseness, NetworKit::ApproxElectricalCloseness, NetworKit::Betweenness, NetworKit::Closeness, NetworKit::CoreDecomposition, NetworKit::DegreeCentrality, NetworKit::DynApproxBetweenness, NetworKit::DynBetweenness, NetworKit::DynKatzCentrality, NetworKit::EigenvectorCentrality, NetworKit::EstimateBetweenness, NetworKit::ForestCentrality, NetworKit::HarmonicCloseness, NetworKit::KPathCentrality, NetworKit::KatzCentrality, NetworKit::LaplacianCentrality, NetworKit::LocalClusteringCoefficient, NetworKit::LocalPartitionCoverage, NetworKit::LocalSquareClusteringCoefficient, NetworKit::PageRank, NetworKit::Sfigality, NetworKit::SpanningEdgeCentrality
Public Functions
Constructs the Centrality class for the given Graph G. If the centrality scores should be normalized, then set normalized to true.
G – The graph.
normalized – If set to true the scores are normalized in the interval [0,1].
computeEdgeCentrality – If true, compute also edge centralities (for algorithms where this is applicable)
Computes centrality scores on the graph passed in constructor.
Get a vector containing the centrality score for each node in the graph.
The centrality scores calculated by run().
Get a vector containing the edge centrality score for each edge in the graph (where applicable).
The edge betweenness scores calculated by run().
Get a vector of pairs sorted into descending order. Each pair contains a node and the corresponding score calculated by run().
A vector of pairs.
Get the centrality score of node v calculated by run().
v – A node.
The betweenness score of node v.
Get the theoretical maximum of centrality score in the given graph.
The maximum centrality score.
Compute the centralization of a network with respect to some centrality measure.
The centralization of any network is a measure of how central its most central node is in relation to how central all the other nodes are. Centralization measures then (a) calculate the sum in differences in centrality between the most central node in a network and all other nodes; and (b) divide this quantity by the theoretically largest such sum of differences in any network of the same size.
centrality index