See centralize() for a summary of graph centralization.
centr_clo(graph, mode = c("out", "in", "all", "total"), normalized = TRUE)The input graph.
This is the same as the mode argument of
closeness().
Logical scalar. Whether to normalize the graph level centrality score by dividing by the theoretical maximum.
A named list with the following components:
The node-level centrality scores.
The graph level centrality index.
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.
Other centralization related:
centr_betw(),
centr_betw_tmax(),
centr_clo_tmax(),
centr_degree(),
centr_degree_tmax(),
centr_eigen(),
centr_eigen_tmax(),
centralize()
# A BA graph is quite centralized
g <- sample_pa(1000, m = 4)
centr_degree(g)$centralization
#> [1] 0.1969036
centr_clo(g, mode = "all")$centralization
#> [1] 0.4825447
centr_betw(g, directed = FALSE)$centralization
#> [1] 0.3384434
centr_eigen(g, directed = FALSE)$centralization
#> [1] 0.954033