Get the alpha centrality values for all nodes in the graph.

get_alpha_centrality(graph, alpha = 1, exo = 1, weights_attr = NULL,
  tol = 1e-07)

Arguments

graph

a graph object of class dgr_graph.

alpha

the parameter that specifies the relative importance of endogenous versus exogenous factors in the determination of centrality.

exo

the exogenous factors, in most cases this is either a constant (which applies the same factor to every node), or a vector giving the factor for every node.

weights_attr

an optional name of the edge attribute to use in the adjacency matrix. If NULL then, if it exists, the weight edge attribute of the graph will be used. Failing that, the standard adjacency matrix will be used in calculations.

tol

the tolerance for near-singularities during matrix inversion. Default value is set to 1e-7.

Value

a data frame with alpha centrality scores for each of the nodes.

Examples

# Create a random graph using the # `add_gnm_graph()` function graph <- create_graph() %>% add_gnm_graph( n = 10, m = 12, set_seed = 23) # Get the alpha centrality scores # for all nodes graph %>% get_alpha_centrality()
#> id alpha_centrality #> 1 1 9 #> 2 2 6 #> 3 3 2 #> 4 4 1 #> 5 5 4 #> 6 6 1 #> 7 7 2 #> 8 8 2 #> 9 9 7 #> 10 10 4
# Add the alpha centrality # scores to the graph as a node # attribute graph <- graph %>% join_node_attrs( df = get_alpha_centrality(.)) # Display the graph's node # data frame graph %>% get_node_df()
#> id type label alpha_centrality #> 1 1 <NA> 1 9 #> 2 2 <NA> 2 6 #> 3 3 <NA> 3 2 #> 4 4 <NA> 4 1 #> 5 5 <NA> 5 4 #> 6 6 <NA> 6 1 #> 7 7 <NA> 7 2 #> 8 8 <NA> 8 2 #> 9 9 <NA> 9 7 #> 10 10 <NA> 10 4