NetworkToolbox (version 1.2.2)

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 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")

# }