See centralize() for a summary of graph centralization.
Usage
centr_clo(graph, mode = c("out", "in", "all", "total"), normalized = TRUE)Arguments
- graph
The input graph.
- mode
This is the same as the
modeargument ofcloseness().- normalized
Logical scalar. Whether to normalize the graph level centrality score by dividing by the theoretical maximum.
Value
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
normalizedargument wasTRUE, then the result was divided by this number.
See also
Other centralization related:
centr_betw(),
centr_betw_tmax(),
centr_clo_tmax(),
centr_degree(),
centr_degree_tmax(),
centr_eigen(),
centr_eigen_tmax(),
centralize()
Examples
# A BA graph is quite centralized
g <- sample_pa(1000, m = 4)
centr_degree(g)$centralization
#> [1] 0.1518135
centr_clo(g, mode = "all")$centralization
#> [1] 0.413991
centr_betw(g, directed = FALSE)$centralization
#> [1] 0.2305906
centr_eigen(g, directed = FALSE)$centralization
#> [1] 0.943837