Skip to contents

Calculate Edge Centrality Measures

Source: R/centrality.R
edge_centrality.Rd

Computes centrality measures for edges in a network and returns a tidy data frame. Unlike node centrality, these measures describe edge importance.

Usage

edge_centrality(
  x,
  measures = "all",
  weighted = TRUE,
  directed = NULL,
  cutoff = -1,
  invert_weights = NULL,
  alpha = 1,
  digits = NULL,
  sort_by = NULL,
  ...
)

edge_betweenness(x, ...)

Arguments

x

Network input (matrix, igraph, network, cograph_network, tna object)

measures

Which measures to calculate. Default "all" calculates all available edge measures. Options: "betweenness", "weight".

weighted

Logical. Use edge weights if available. Default TRUE.

directed

Logical or NULL. If NULL (default), auto-detect from matrix symmetry. Set TRUE to force directed, FALSE to force undirected.

cutoff

Maximum path length for betweenness. Default -1 (no limit).

invert_weights

Logical or NULL. Invert weights for path-based measures? Default NULL (auto-detect: TRUE for tna objects, FALSE otherwise).

alpha

Numeric. Exponent for weight inversion. Default 1.

digits

Integer or NULL. Round numeric columns. Default NULL.

sort_by

Character or NULL. Column to sort by (descending). Default NULL.

...

Additional arguments passed to to_igraph

Value

A data frame with columns:

  • from: Source node label

  • to: Target node label

  • weight: Edge weight (if weighted)

  • betweenness: Edge betweenness centrality

Named numeric vector of edge betweenness values (named by "from->to").

Details

Edge centrality measures available:

betweenness

Number of shortest paths passing through the edge. Edges with high betweenness are bridges connecting different parts of the network.

weight

Original edge weight (included for reference)

Examples

# Create test network
mat <- matrix(c(0,1,1,0, 1,0,1,1, 1,1,0,0, 0,1,0,0), 4, 4)
rownames(mat) <- colnames(mat) <- c("A", "B", "C", "D")

# All edge measures
edge_centrality(mat)
#>   from to weight betweenness
#> 1    A  B      1           2
#> 2    A  C      1           1
#> 3    B  C      1           2
#> 4    B  D      1           3

# Just betweenness
edge_centrality(mat, measures = "betweenness")
#>   from to betweenness
#> 1    A  B           2
#> 2    A  C           1
#> 3    B  C           2
#> 4    B  D           3

# Sort by betweenness to find bridge edges
edge_centrality(mat, sort_by = "betweenness")
#>   from to weight betweenness
#> 1    B  D      1           3
#> 2    A  B      1           2
#> 3    B  C      1           2
#> 4    A  C      1           1
mat <- matrix(c(0,1,1,0, 1,0,1,1, 1,1,0,0, 0,1,0,0), 4, 4)
rownames(mat) <- colnames(mat) <- c("A", "B", "C", "D")
edge_betweenness(mat)
#> A->B A->C B->C B->D 
#>    2    1    2    3