Computes betweenness centrlaity based on randomized shortest paths of each node in a network (Please see and cite Kivimaki et al., 2016)
rspbc(A, beta = 0.01)
An adjacency matrix of network data
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)
A vector of randomized shortest paths betweenness centrality values for each node in the network
Kivimaki, I., Lebichot, B., Saramaki, J., & Saerens, M. (2016). Two betweenness centrality measures based on Randomized Shortest Paths. Scientific Reports, 6(19668), 1-15.
# NOT RUN {
A<-TMFG(neoOpen)$A
rspbc<-rspbc(A, beta=0.01)
# }
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