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 theoratical 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