met.eigen.single: Eigenvector Centrality

In SebastianSosa/ANTs: Animal Network Toolkit Software

Eigenvector Centrality

Description

Calculate for all the vertices the node metric call met.evcent centrality.

Usage

met.eigen.single(
  M,
  df = NULL,
  dfid = NULL,
  sym = TRUE,
  binary = FALSE,
  out = FALSE
)

Arguments

M	a square adjacency matrix.
df	a data frame of same length of the input matrix.
dfid	an integer indicating the column of individual ids in argument df

Details

met.evcent centrality is the first non-negative met.evcent value obtained through the linear transformation of an adjacency matrix. This centrality measure quantifies not only a node connectedness, but also the connections of the nodes to whom it is connected. Thus, a node can have a high met.evcent value by having a high met.degree or met.strength, or by being connected to nodes that have high degrees or strengths.

Value

Integer vector of each met.evcent centrality.

Author(s)

Sebastian Sosa, Ivan Puga-Gonzalez

References

Whitehead, H. A. L. (1997). Analysing animal social structure. Animal behaviour, 53(5), 1053-1067.

Sosa, S. (2018). Social Network Analysis, in: Encyclopedia of Animal Cognition and Behavior. Springer.

SebastianSosa/ANTs documentation built on Sept. 25, 2023, 11:06 p.m.