Use this if you are using igraph from R
| centr_degree {igraph} | R Documentation | 
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