See centralize()
for a summary of graph centralization.
Arguments
- graph
The input graph. It can also be
NULL
, ifnodes
is given.- nodes
The number of vertices. This is ignored if the graph is given.
- directed
logical scalar, whether to use directed shortest paths for calculating betweenness.
- scale
Whether to rescale the eigenvector centrality scores, such that the maximum score is one.
Value
Real scalar, the theoretical maximum (unnormalized) graph betweenness centrality score for graphs with given order and other parameters.
See also
Other centralization related:
centr_betw()
,
centr_betw_tmax()
,
centr_clo()
,
centr_clo_tmax()
,
centr_degree()
,
centr_degree_tmax()
,
centr_eigen()
,
centralize()
Examples
# A BA graph is quite centralized
g <- sample_pa(1000, m = 4)
centr_eigen(g, normalized = FALSE)$centralization %>%
`/`(centr_eigen_tmax(g))
#> [1] 0.9386488
centr_eigen(g, normalized = TRUE)$centralization
#> [1] 0.9386488