mreach.degree: Compute the M-reach Degree Centrality Score in a Netwrok

In keyplayer: Locating Key Players in Social Networks

Compute the M-reach Degree Centrality Score in a Netwrok

Description

mreach.degree computes the size of reachable nodes from a particular node within M steps. M-reach degree centrality generalizes the degree centrality by delimiting specific neighborhoods.

Usage

mreach.degree(
  adj.matrix,
  node,
  M = Inf,
  binary = TRUE,
  cmode = "all",
  large = TRUE,
  geodist.precomp = NULL
)

Arguments

adj.matrix	Matrix indicating the adjacency matrix of the network.
node	Integer indicating the column index of the chosen player in the adjacenncy matrix. If not specified, scores for all nodes will be reported.
M	Number indicating the maximum geodistance between two nodes, above which the two nodes are considered disconnected. M hence defines the reachable set. The default is Inf.
binary	Logical scalar. If TRUE, the adjacency matrix is binarized, and thus M essentially means steps. If FALSE, the edge values are considered.
cmode	String indicating the type of centrality being evaluated. "outdegree", "indegree", and "total" refer to indegree, outdegree, and (total) degree respectively. "all" reports all the above measures and is the default.
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).

Details

The interprtation of the measure in binary and weighted adjacency matrix are slightly different. In binary networks, the reachable set of nodes is defined by nodes that are reachable within M steps. In weighted networks, the reachable set is defined by nodes that are reachable within geodistance M.

Value

A vector indicating the outdegree, indegree, or total-degree mreach.degree score of the chosen node; or a data frame containing all the above information.

Author(s)

Weihua An [e-mail]; Yu-Hsin Liu [e-mail]

References

An, Weihua and Yu-Hsin Liu (2016). "keyplayer: An R Package for Locating Key Players in Social Networks." The R Journal, 8(1): 257-268.

Butts, Carter T. (2014). sna: Tools for Social Network Analysis. R package version 2.3-2. https://cran.r-project.org/package=sna

Csardi, G and Nepusz, T (2006). "The igraph software package for complex network research." InterJournal, Complex Systems 1695. https://igraph.org/

See Also

geodist; shortest.paths; mreach.closeness; kpcent; kpset

Examples

# Create a 5x5 weighted and directed adjacency matrix,
# where edge values represent the strength of tie
W <- matrix(
  c(0,1,3,0,0,
    0,0,0,4,0,
    1,1,0,2,0,
    0,0,0,0,3,
    0,2,0,0,0),
    nrow=5, ncol=5, byrow = TRUE)


# List the 2-reach degree scores for every node where W is binarized
mreach.degree(W,M=2,cmode="all",large=FALSE)

keyplayer documentation built on Nov. 8, 2023, 9:06 a.m.