NetworkToolbox (version 1.2.3)

rspbc: Randomized Shortest Paths Betweenness Centrality

Description

Computes betweenness centrlaity based on randomized shortest paths of each node in a network (Please see and cite Kivimaki et al., 2016)

Usage

rspbc(A, beta = 0.01)

Arguments

A

An adjacency matrix of network data

beta

Sets the beta parameter. Defaults to 0.01 (recommended). Beta > 0.01 measure gets closer to weighted betweenness centrality (10) and beta < 0.01 measure gets closer to degree (.0001)

Value

A vector of randomized shortest paths betweenness centrality values for each node in the network

References

Kivimaki, I., Lebichot, B., Saramaki, J., & Saerens, M. (2016). Two betweenness centrality measures based on Randomized Shortest Paths. Scientific Reports, 6, 19668. doi: 10.1038/srep19668

Examples

# NOT RUN {
A <- TMFG(neoOpen)$A

rspbc <- rspbc(A, beta=0.01)

# }