edge_centrality: Calculate Edge Centrality Measures

In cograph: Analysis and Visualization of Complex Networks

Calculate Edge Centrality Measures

Description

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", "overlap", "simmelian", "reciprocity".
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

Details

Edge measures available:

betweenness

Number of shortest paths passing through the edge.

weight

Original edge weight.

overlap

Jaccard neighborhood overlap of edge endpoints.

simmelian

Number of triangles the edge participates in.

reciprocity

Whether the reverse edge exists (directed only). Adds columns: reciprocated, reverse_weight, weight_ratio.

Value

A data frame with columns from, to, and one column per requested measure.

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

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)

# Just betweenness
edge_centrality(mat, measures = "betweenness")

# Sort by betweenness to find bridge edges
edge_centrality(mat, sort_by = "betweenness")
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)

cograph documentation built on May 31, 2026, 5:06 p.m.