See centralize
for a summary of graph centralization.
centr_betw(graph, directed = TRUE, nobigint = TRUE, normalized = TRUE)
The input graph.
logical scalar, whether to use directed shortest paths for calculating betweenness.
Logical scalar, whether to use big integers for the
betweenness calculation. This argument is passed to the
betweenness
function.
Logical scalar. Whether to normalize the graph level centrality score by dividing by the theoretical maximum.
A named list with the following components:
The node-level centrality scores.
The graph level centrality index.
The maximum theoretical graph level
centralization score for a graph with the given number of vertices,
using the same parameters. If the normalized
argument was
TRUE
, then the result was divided by this number.
Other centralization related:
centr_betw_tmax()
,
centr_clo_tmax()
,
centr_clo()
,
centr_degree_tmax()
,
centr_degree()
,
centr_eigen_tmax()
,
centr_eigen()
,
centralize()
# NOT RUN {
# 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
# }
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