Catalogue of the Centrality Measures

Returns a table of every measure centrality can compute. For each measure the table records which end of the scale marks a prominent node, whether the measure accepts mode, whether it requires a community partition, whether it uses edge weights, and whether type = "all" holds it back because its cost grows steeply with network size.

Usage

list_centralities(orientation = NULL, costly = NULL, needs_membership = NULL)

Arguments

orientation

Keep only measures with this orientation: "higher" or "lower". Default NULL keeps both.

costly

Keep only costly measures (TRUE) or only the rest (FALSE). Default NULL keeps both.

needs_membership

Keep only measures that require a partition (TRUE) or only those that do not (FALSE). Default NULL keeps both.

Value

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.

Details

For some measures a low value marks the more central node, so a descending sort of their column places the most peripheral nodes first. orientation = "lower" lists them.

See also

centrality to compute them, centrality_degree and the other one-measure verbs.

Examples

list_centralities(orientation = "lower")
#>                   measure orientation mode_aware needs_membership uses_weights
#> 1      access_information       lower      FALSE            FALSE        FALSE
#> 2        average_distance       lower       TRUE            FALSE         TRUE
#> 3              constraint       lower      FALSE            FALSE         TRUE
#> 4            eccentricity       lower       TRUE            FALSE         TRUE
#> 5                 heatmap       lower       TRUE            FALSE        FALSE
#> 6        hide_information       lower      FALSE            FALSE        FALSE
#> 7         local_dimension       lower       TRUE            FALSE        FALSE
#> 8   local_dimension_fixed       lower       TRUE            FALSE        FALSE
#> 9           local_entropy       lower       TRUE            FALSE        FALSE
#> 10 local_volume_dimension       lower       TRUE            FALSE        FALSE
#> 11           second_order       lower      FALSE            FALSE        FALSE
#> 12                 wiener       lower       TRUE            FALSE         TRUE
#>    costly
#> 1   FALSE
#> 2   FALSE
#> 3   FALSE
#> 4   FALSE
#> 5   FALSE
#> 6   FALSE
#> 7   FALSE
#> 8   FALSE
#> 9   FALSE
#> 10  FALSE
#> 11  FALSE
#> 12  FALSE