NetworkToolbox (version 1.1.2)

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, factors = c("walktrap", "louvain"))

Arguments

A

Network adjacency matrix

factors

A vector of corresponding to each item's factor. 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 factors (see examples)

Value

Returns a list of overall (signs not considered; overall), negative (negative), and positive (positive) participation coefficient. 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(7028), 895-900.

Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. Neuroimage, 52(3), 1059-1069.

Examples

# NOT RUN {
#theoretical factors
factors <- 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, factors = factors)

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