LeaderRank Centrality

LeaderRank (Lu et al. 2011) adds a ground node joined in both directions to every node and runs a random walk without damping on the extended network. The final score of the ground node is shared equally among the other nodes.

Usage

centrality_leaderrank(x, ...)

Arguments

x: Network input accepted by centrality.
...: Further arguments to centrality.

Value

A named numeric vector with one score per node, in input node order.

Details

The measure needs a directed network. On undirected input every score is NA with a cograph_undefined_measure warning. Edge weights are ignored; centrality_weighted_leaderrank uses them. The walk starts with one unit at every node and none at the ground node, so the scores sum to \(n\). The values equal centiserve::leaderrank().

References

Lu, L., Zhang, Y.-C., Yeung, C. H., & Zhou, T. (2011). Leaders in social networks, the Delicious case. PLoS ONE, 6(6), e21202. doi:10.1371/journal.pone.0021202 .

Examples

centrality_leaderrank(regulation_net)
#>    Explore       Plan    Monitor      Adapt    Reflect    Discuss Synthesize 
#>  1.2831245  0.7493777  1.4385276  1.1627388  1.1517175  0.7553269  0.6661930 
#>   Evaluate     Create      Share 
#>  0.6876645  1.0614717  1.0438580