subgraph.centrality: 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
subgraph.centrality (graph, diag=FALSE)
Arguments
graph
The input graph, it should be undirected, but the
implementation does not check this currently.
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.
Value
A numeric vector, the subgraph centrality scores of the vertices.
concept
Subgraph centrality
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.
References
Ernesto Estrada, Juan A. Rodriguez-Velazquez: Subgraph centrality in
Complex Networks. Physical Review E 71, 056103 (2005).