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