Centralize a graph according to the degrees of vertices — centr_degree • igraph

See centralize() for a summary of graph centralization.

Usage

centr_degree(
  graph,
  mode = c("all", "out", "in", "total"),
  loops = TRUE,
  normalized = TRUE
)

Arguments

graph: The input graph.
mode: This is the same as the mode argument of degree().
loops: Logical scalar, whether to consider loops edges when calculating the degree.
normalized: Logical scalar. Whether to normalize the graph level centrality score by dividing by the theoretical maximum.

Value

A named list with the following components:

res: The node-level centrality scores.
centralization: The graph level centrality index.
theoretical_max: The maximum theoretical graph level centralization score for a graph with the given number of vertices, using the same parameters. If the normalized argument was TRUE, then the result was divided by this number.

See also

Other centralization related: centr_betw(), centr_betw_tmax(), centr_clo(), centr_clo_tmax(), centr_degree_tmax(), centr_eigen(), centr_eigen_tmax(), centralize()

igraph_centralization_degree().

Examples

# A BA graph is quite centralized
g <- sample_pa(1000, m = 4)
centr_degree(g)$centralization
#> [1] 0.1638375
centr_clo(g, mode = "all")$centralization
#> [1] 0.4236249
centr_betw(g, directed = FALSE)$centralization
#> [1] 0.2452183
centr_eigen(g, directed = FALSE)$centralization
#> [1] 0.941744