Centralize a graph according to the eigenvector centrality of vertices

centralization.evcent() was renamed to centr_eigen() to create a more consistent API.

Usage

centralization.evcent(
  graph,
  directed = FALSE,
  scale = TRUE,
  options = arpack_defaults(),
  normalized = TRUE
)

graph: The input graph.
directed: logical scalar, whether to use directed shortest paths for calculating eigenvector centrality.
scale: Ignored. Computing eigenvector centralization requires normalized eigenvector centrality scores.
options: This is passed to eigen_centrality(), the options for the ARPACK eigensolver.
normalized: Logical scalar. Whether to normalize the graph level centrality score by dividing by the theoretical maximum.