NetworkToolbox (version 1.2.3)

participation: Participation Coefficient

Description

Computes the participation coefficient for each node. The participation coefficient measures the strength of a node's connections within its community. Positive and negative signed weights for participation coefficients are computed separately.

Usage

participation(A, comm = c("walktrap", "louvain"))

Arguments

A

Network adjacency matrix

comm

A vector of corresponding to each item's community. Defaults to "walktrap" for the cluster_walktrap community detection algorithm. Set to "louvain" for the louvain community detection algorithm. Can also be set to user-specified communities (see examples)

Value

Returns a list containing:

overall

Participation coefficient without signs considered

positive

Participation coefficient with only positive sign

negative

Participation coefficient wih only negative sign

Details

Values closer to 1 suggest greater within-community connectivity and values closer to 0 suggest greater between-community connectivity

References

Guimera, R., & Amaral, L. A. N. (2005). Functional cartography of complex metabolic networks. Nature, 433, 895-900. doi: 10.1038/nature03288

Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. Neuroimage, 52, 1059-1069. doi: 10.1016/j.neuroimage.2009.10.003

Examples

# NOT RUN {
#theoretical factors
comm <- c(rep(1,8), rep(2,8), rep(3,8), rep(4,8), rep(5,8), rep(6,8))

A <- TMFG(neoOpen)$A

pc <- participation(A, comm = comm)

#walktrap factors
wpc <- participation(A, comm = "walktrap")

# }