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 forwarded to the graph constructor, namely loops and simplify (see centrality).

Details

Edge measures available, with the column(s) each one adds:

betweenness

Number of shortest paths passing through the edge. Adds betweenness.

weight

Original edge weight (1 for an unweighted input). Adds weight.

overlap

Jaccard neighborhood overlap of the edge endpoints. Adds overlap and the raw count shared_neighbors.

simmelian

Number of triangles the edge participates in. Adds triangles (there is no column called simmelian).

reciprocity

Whether the reverse edge exists. Directed only: on an undirected input it warns and adds nothing. Adds reciprocated, reverse_weight and weight_ratio, the last two NA where the edge is not reciprocated.

measures = "all" requests every measure, dropping reciprocity on an undirected input.

Value

A base data.frame with one row per edge, in the canonical (row-major) edge order of the input. The first two columns are from and to (character when the input carried node names, numeric indices otherwise); the remaining columns are those the requested measures contribute, as listed in Details. measures = "all" on an undirected input therefore gives from, to, weight, betweenness, overlap, shared_neighbors and triangles, and a directed input adds reciprocated, reverse_weight and weight_ratio.

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 Sept. 30, 2026, 5:08 p.m.