Use this if you are using igraph from R
See centralize
for a summary of graph centralization.
centr_betw(graph, directed = TRUE, nobigint = TRUE, normalized = TRUE)
graph 
The input graph. 
directed 
logical scalar, whether to use directed shortest paths for calculating betweenness. 
nobigint 
Logical scalar, whether to use big integers for the
betweenness calculation. This argument is passed to the

normalized 
Logical scalar. Whether to normalize the graph level centrality score by dividing by the theoretical maximum. 
A named list with the following components:
res 
The nodelevel 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 
Other centralization related:
centr_betw_tmax()
,
centr_clo_tmax()
,
centr_clo()
,
centr_degree_tmax()
,
centr_degree()
,
centr_eigen_tmax()
,
centr_eigen()
,
centralize()
# A BA graph is quite centralized g < sample_pa(1000, m = 4) centr_degree(g)$centralization centr_clo(g, mode = "all")$centralization centr_betw(g, directed = FALSE)$centralization centr_eigen(g, directed = FALSE)$centralization