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