Use this if you are using igraph from R
See centralize
for a summary of graph centralization.
centr_eigen_tmax(graph = NULL, nodes = 0, directed = FALSE, scale = TRUE)
graph |
The input graph. It can also be |
nodes |
The number of vertices. This is ignored if the graph is given. |
directed |
logical scalar, whether to use directed shortest paths for calculating betweenness. |
scale |
Whether to rescale the eigenvector centrality scores, such that the maximum score is one. |
Real scalar, the theoretical maximum (unnormalized) graph betweenness centrality score for graphs with given order and other parameters.
Other centralization related:
centr_betw_tmax()
,
centr_betw()
,
centr_clo_tmax()
,
centr_clo()
,
centr_degree_tmax()
,
centr_degree()
,
centr_eigen()
,
centralize()
# A BA graph is quite centralized g <- sample_pa(1000, m = 4) centr_eigen(g, normalized = FALSE)$centralization %>% `/`(centr_eigen_tmax(g)) centr_eigen(g, normalized = TRUE)$centralization