Use this if you are using igraph from R
See centralize for a summary of graph centralization.
centr_degree(graph, mode = c("all", "out", "in", "total"),
  loops = TRUE, normalized = TRUE)
graph | 
 The input graph.  | 
mode | 
 This is the same as the   | 
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.  | 
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_betw, centr_clo_tmax,
centr_clo, centr_degree_tmax,
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