group.mreach.closeness: Compute the Group-level mreach.closeness Centrality Score in...
In keyplayer: Locating Key Players in Social Networks

group.mreach.closeness

R Documentation

Compute the Group-level mreach.closeness Centrality Score in a Netwrok

Description

mreach.closeness refines the mreach.degree centrality by using the (inverse) geodistance as weights. The edge values should be properly interpreted as distances.

Usage

group.mreach.closeness(
  adj.matrix,
  nodes,
  M = Inf,
  method = "min",
  binary = FALSE,
  cmode = "total",
  large = TRUE,
  geodist.precomp = NULL
)

Arguments

`adj.matrix`	Matrix indicating the adjacency matrix of the network.
`nodes`	Integer indicating the column index of the chosen player in the adjacenncy matrix. If there are multiple players, use `c(index1,index2,...)`
`M`	Number indicating the maximum distance between two nodes, above witch the two nodes are considered disconnected. The default is `Inf`.
`method`	Indication of which grouping criterion should be used. `method="min"` indicates the "minimum" criterion (edge values as distances). `method="max"` indicates the "maximum" criterion (edge values as non-cummulative strengths). `method="add"` indicates the "addition" criterion (edge values as cummulative strengths). `method="union"` indicates the "union" criterion (edge values as probability). The default is the "minimum" criterion for mrach.closeness centrality.
`binary`	If `TRUE`, the adjacency matrix is binarized. If `FALSE`, the edge values are considered.
`cmode`	String indicating the type of centrality being evaluated. The default is to report the total degree. `"outdegree"` and `"indegree"` refer to indegree and outdegree respectively. If `"all"`, all the three types are reported.
`large`	Logical scalar, whether the computation method for large network is implemented. If `TRUE` (the default), the method implmented in igraph is used; otherwise the method implemented in sna is used.
`geodist.precomp`	Geodistance precomputed for the graph to be analyzed (optional).

Value

A vector indicating the outdegree, indegree, or total-degree cohesion score of the chosen players; or a data frame containing all the above information. Note that the outdegree and indegree scores are normalized to [0,1]. This means that the total-degree score is between [0,2].