weighted_richclub_tm: The weighted rich-club effect (two-mode networks)

Description

This function calculates the weighted rich-club coefficient proposed in Opsahl, T., Colizza, V., Panzarasa, P., Ramasco, J.J., 2008. Prominence and control: The weighted rich-club effect. PRL 101. It incorporates two extentions explained in this blog post http://toreopsahl.com/2009/05/29/weighted-rich-club-effect-a-more-appropriate-null-model-for-scientific-collaboration-networks/: 1) a new way of reshuffling (two-mode link reshuffling; 2) calculating significance levels if there are more than 100 random networks (see my PhD thesis; http://toreopsahl.com/publications/thesis/)

Usage

weighted_richclub_tm(net, NR=1000, seed=NULL, projection.method="Newman", nbins=30)

Arguments

net

A binary two-mode edgelist

number of random networks used.

seed

the random generators seed, used to produce random yet reproducable results.

projection.method

the method used to project the two-mode network to a weighted one-mode network: either "sum" or "Newman"

nbins

the number of bins in the output

Value

Returns a table with the fraction of phi(observed) over phi(null). Nbins controls the number of rows.

References

Opsahl et al., 2008. Prominence and control: The weighted rich-club effect. PRL 101 http://toreopsahl.com/2008/12/12/article-prominence-and-control-the-weighted-rich-club-effect/ http://toreopsahl.com/2009/05/29/weighted-rich-club-effect-a-more-appropriate-null-model-for-scientific-collaboration-networks/

Examples

Run this code

# NOT RUN {
## Load  data
data(tnet)

## Run the function on a subset
weighted_richclub_tm(Newman.Condmat.95.99.net.2mode[1:100,], NR=10)

# }