summary_centrality_subgraph: Find subgraph centrality scores of network positions

View source: R/summary_centrality_subgraph.R

summary_centrality_subgraphR Documentation

Find subgraph centrality scores of network positions

Description

Subgraph centrality of a vertex measures the number of subgraphs a vertex participates in, weighting them according to their size.

Usage

summary_centrality_subgraph(graph, diag = FALSE)

Arguments

graph

The input graph assuming it is undirected

diag

Boolean scalar, whether to include the diagonal of the adjacency matrix in the analysis. Giving 'FALSE' here effectively eliminates the loops edges from the graph before the calculation.

Details

The subgraph centrality of a vertex is defined as the number of closed loops originating at the vertex, where longer loops are exponentially downweighted.

Currently the calculation is performed by explicitly calculating all eigenvalues and eigenvectors of the adjacency matrix of the graph. This effectively means that the measure can only be calculated for small graphs.

Value

A numeric vector, the subgraph centrality scores of the vertices.

Author(s)

Tobias Woertwein based on Gabor Csardi based on the Matlab code by Ernesto Estrada

References

Ernesto Estrada, Juan A. Rodriguez-Velazquez: Subgraph centrality in Complex Networks. *Physical Review E* 71, 056103 (2005).

See Also

Other centrality: summary_centrality_alpha(), summary_centrality_harmonic()


drostlab/edgynode documentation built on March 29, 2024, 10:36 a.m.