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 with 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.
Rubinov, M., & Sporns, O. (2010).
Complex network measures of brain connectivity: Uses and interpretations.
Neuroimage, 52, 1059-1069.
# NOT RUN {#theoretical factorscomm <- rep(1:8, each = 6)
A <- TMFG(neoOpen)$A
pc <- participation(A, comm = comm)
#walktrap factorswpc <- participation(A, comm = "walktrap")
# }