Computes centrality measures for the edges of a network and returns a tidy data frame with one row per edge.
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, edge-list data frame, 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. Whether edge betweenness inverts the weights, so that higher weights mean shorter paths. The default
NULLis TRUE for tna objects and FALSE otherwise.- alpha
Numeric. Exponent of the inversion, which computes distances as
1 / weight^alpha. Default 1.- digits
Integer or NULL. Round numeric columns. Default NULL.
- sort_by
Character or NULL. Column to sort by (descending). Default NULL.
- ...
For
edge_centrality(), the graph-construction argumentsloopsandsimplify(seecentrality). Foredge_betweenness(), arguments passed toedge_centrality().
Value
edge_centrality() returns 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.
edge_betweenness() returns a numeric vector of edge
betweenness values named "from->to", for directed and undirected
inputs alike.
Details
Edge measures available, with the column(s) each one adds:
- betweenness
Edge betweenness, the sum over node pairs of the share of their shortest paths that pass 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
overlapand the raw countshared_neighbors.- simmelian
Number of triangles the edge participates in. Adds
triangles(there is no column calledsimmelian).- reciprocity
Whether the reverse edge exists. Directed only: on an undirected input it warns and adds nothing. Adds
reciprocated,reverse_weightandweight_ratio, the last twoNAwhere the edge is not reciprocated.
measures = "all" requests every measure, dropping
reciprocity on an undirected input.
Examples
edge_centrality(regulation_net, measures = "betweenness")
#> from to betweenness
#> 1 Explore Reflect 3.0
#> 2 Explore Share 11.0
#> 3 Plan Monitor 4.0
#> 4 Plan Discuss 4.0
#> 5 Plan Evaluate 7.0
#> 6 Plan Create 7.5
#> 7 Plan Share 2.0
#> 8 Monitor Adapt 21.0
#> 9 Monitor Create 6.0
#> 10 Adapt Explore 3.0
#> 11 Adapt Discuss 5.5
#> 12 Adapt Synthesize 15.5
#> 13 Reflect Explore 6.0
#> 14 Reflect Monitor 13.0
#> 15 Discuss Explore 0.0
#> 16 Discuss Reflect 1.0
#> 17 Discuss Create 8.5
#> 18 Synthesize Plan 9.5
#> 19 Synthesize Monitor 3.0
#> 20 Synthesize Reflect 3.0
#> 21 Evaluate Monitor 0.0
#> 22 Evaluate Adapt 0.0
#> 23 Evaluate Reflect 12.0
#> 24 Create Explore 5.0
#> 25 Create Monitor 7.0
#> 26 Create Evaluate 5.0
#> 27 Create Share 5.0
#> 28 Share Plan 15.0
#> 29 Share Monitor 0.0
#> 30 Share Adapt 3.0