View source: R/centrality-metadata.R
| list_centralities | R Documentation |
A tidy table of every measure centrality can compute, with
the facts you need before you read a column of results: which end of the
scale marks a prominent node, whether the measure needs a community
partition, whether it reads edge weights, and whether it is held back
from type = "all" because its cost grows steeply.
list_centralities(orientation = NULL, costly = NULL, needs_membership = NULL)
orientation |
Keep only measures with this orientation:
|
costly |
Keep only costly measures ( |
needs_membership |
Keep only measures that require a partition
( |
Twelve measures are oriented so that a low value marks the more
central node, and sorting their column the usual way puts the periphery on top.
Filter with orientation = "lower" to see them.
A data.frame with one row per measure and the columns
measure (the name to pass to centrality(measures = )),
orientation ("higher" or "lower", which end of
the scale marks a prominent node), mode_aware (whether the
measure accepts mode and its column carries a mode suffix),
needs_membership, uses_weights, and costly
(held back from type = "all"; add it with
include = ). Rows are ordered by measure name.
centrality to compute them,
centrality_degree and the other one-measure verbs.
# Every measure, with the facts needed to read its column
head(list_centralities())
# The measures where a low value marks the more central node
list_centralities(orientation = "lower")
# The measures held back from type = "all"
list_centralities(costly = TRUE)
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