Edge betweenness centrality — net_edge

For each edge, the share of weighted shortest paths (across all node pairs) that pass through it - a high value marks an edge that bridges otherwise distant parts of the network. Geodesics are computed on inverse absolute weights, so strong edges count as short, matching net_centralities()'s node betweenness/closeness.

Usage

net_edge_betweenness(x, invert = TRUE, labels = NULL)

Arguments

x: A psychnet object or a square weighted adjacency matrix.
invert: If TRUE (default) edge weights are inverted to distances (strong association = short path). Set FALSE to treat weights as distances.
labels: Optional node labels (used when x is a bare matrix).

Value

A tidy data.frame, one row per edge: from, to, edge_betweenness. Undirected networks give one row per unordered edge.

Examples

S <- 0.4^abs(outer(1:6, 1:6, "-"))
net_edge_betweenness(ebic_glasso(cor_matrix = S, n = 400))
#>   from to edge_betweenness
#> 1   V1 V2                5
#> 2   V2 V3                8
#> 3   V3 V4                9
#> 4   V4 V5                8
#> 5   V5 V6                5