eigen_centrality_signed: Signed Eigenvector centrality

In signnet: Methods to Analyse Signed Networks

Signed Eigenvector centrality

Description

returns the eigenvector associated with the dominant eigenvalue from the adjacency matrix.

Usage

eigen_centrality_signed(g, scale = TRUE)

Arguments

g	igraph object with a sign edge attribute.
scale	Logical scalar, whether to scale the result to have a maximum score of one. If no scaling is used then the result vector is the same as returned by eigen().

Details

Note that, with negative values, the adjacency matrix may not have a dominant eigenvalue. This means it is not clear which eigenvector should be used. In addition it is possible for the adjacency matrix to have repeated eigenvalues and hence multiple linearly independent eigenvectors. In this case certain centralities can be arbitrarily assigned. The function returns an error if this is the case.

Value

centrality scores as numeric vector.

Author(s)

David Schoch

References

Bonacich, P. and Lloyd, P. (2004). "Calculating Status with Negative Relations." Social Networks 26 (4): 331–38.

Everett, M. and Borgatti, S.P. (2014). "Networks Containing Negative Ties." Social Networks 38: 111–20.

Examples

library(igraph)
data("tribes")
eigen_centrality_signed(tribes)

signnet documentation built on Sept. 9, 2023, 1:06 a.m.