Get the leverage centrality values for all nodes in the graph. Leverage centrality is a measure of the relationship between the degree of a given node and the degree of each of its neighbors, averaged over all neighbors. A node with negative leverage centrality is influenced by its neighbors, as the neighbors connect and interact with far more nodes. A node with positive leverage centrality influences its neighbors since the neighbors tend to have far fewer connections.
Examples
# Create a random graph using the
# `add_gnm_graph()` function
graph <-
create_graph(
directed = FALSE) %>%
add_gnm_graph(
n = 10,
m = 15,
set_seed = 23)
# Get leverage centrality values
# for all nodes in the graph
graph %>%
get_leverage_centrality()
#> id leverage_centrality
#> 1 1 -0.1964
#> 2 2 -0.1964
#> 3 3 -0.3810
#> 4 4 0.0556
#> 5 5 -0.0556
#> 6 6 0.0556
#> 7 7 -0.1964
#> 8 8 -0.3810
#> 9 9 -0.1964
#> 10 10 -1.0000
# Add the leverage centrality
# values to the graph as a
# node attribute
graph <-
graph %>%
join_node_attrs(
df = get_leverage_centrality(.))
# Display the graph's node data frame
graph %>% get_node_df()
#> id type label leverage_centrality
#> 1 1 <NA> 1 -0.1964
#> 2 2 <NA> 2 -0.1964
#> 3 3 <NA> 3 -0.3810
#> 4 4 <NA> 4 0.0556
#> 5 5 <NA> 5 -0.0556
#> 6 6 <NA> 6 0.0556
#> 7 7 <NA> 7 -0.1964
#> 8 8 <NA> 8 -0.3810
#> 9 9 <NA> 9 -0.1964
#> 10 10 <NA> 10 -1.0000