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 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  | 
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