gateway: Gateway Coefficient

In NetworkToolbox: Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis

Description

Computes the gateway coefficient for each node. The gateway coefficient measures a node's connections between its community and other communities. Nodes that are solely responsible for inter-community connectivity will have higher gateway coefficient values. Positive and negative signed weights for gateway coefficients are computed separately.

Usage

gateway(
  A,
  comm = c("walktrap", "louvain"),
  cent = c("strength", "betweenness")
)

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)
cent	Centrality to community gateway coefficient. Defaults to "strength". Set to "betweenness" to use the betweenness centrality

Value

Returns a list containing:

overall	Gateway coefficient without signs considered
positive	Gateway coefficient with only positive sign
negative	Gateway coefficient with only negative sign

Author(s)

Alexander Christensen <[e-mail]>

References

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

Vargas, E. R., & Wahl, L. M. (2014). The gateway coefficient: A novel metric for identifying critical connections in modular networks. The European Physical Journal B, 87, 1-10.

Examples

#theoretical communities
comm <- rep(1:8, each = 6)

# Pearson's correlation only for CRAN checks
A <- TMFG(neoOpen, normal = FALSE)$A

gw <- gateway(A, comm = comm)

#walktrap communities
wgw <- gateway(A, comm = "walktrap")

NetworkToolbox documentation built on May 28, 2021, 5:11 p.m.