Description Usage Arguments Details Value Author(s) References See Also Examples
mreach.closeness
refines the mreach.degree
centrality by
using the (inverse) geodistance as weights.
The edge values should be properly interpreted as distances.
1 2  mreach.closeness(adj.matrix, node, M = Inf, binary = FALSE, cmode = "all",
large = TRUE, geodist.precomp = NULL)

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 witch the two nodes are considered disconnected.
M hence defines the reachable set. The default is 
binary 
Logical scalar. If 
cmode 
String indicating the type of centrality being evaluated.

large 
Logical scalar, whether the computation method for large network is
implemented. If 
geodist.precomp 
Geodistance precomputed for the graph to be analyzed (optional). 
mreach.closeness
refines the mreach.degree
centrality
by using the (inverse) geodistance as weights, just as closeness
centrality refines degree
centrality.
It captures the degree centrality when M is properly set (e.g. M=1 in a binarized network).
It captures the GilSchmidt power index (Gil and Schmidt, 1996)
and the cohesion centrality (Borgatti, 2006) when M is sufficiently large
(unconstrained). The normalization factor takes care of nonbinary
edge values. Also note that the geodistance matrix does
not necessarily to be symmetric.
A vector indicating the outdegree, indegree, or totaldegree cohesion score of the chosen player; 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 totaldegree score is between [0,2].
Weihua An [email protected]; YuHsin Liu [email protected]
An, Weihua and YuHsin Liu (2016). "keyplayer: An R Package for Locating Key Players in Social Networks."
Working Paper, Indiana Univeristy.
Borgatti, Stephen P. (2006). "Identifying Sets of Key Players in a Network."
Computational, Mathematical and Organizational Theory, 12(1):2134.
Butts, Carter T. (2014). sna: Tools for Social Network Analysis. R package
version 2.32. http://CRAN.Rproject.org/package=sna
Csardi, G and Nepusz, T (2006). "The igraph software package for complex network research."
InterJournal, Complex Systems 1695. http://igraph.org
Gil, J and Schmidt, S (1996). "The Origin of the Mexican Network of Power."
Proceedings of the International Social Network Conference, Charleston, SC, 2225.
geodist
;
shortest.paths
;
mreach.degree
;
kpcent
;
kpset
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  # 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)
# Transform the edge value to distance interpretaion
A < W
A[W!=0] < 1/W[W!=0]
# List all types of 2reach closeness scores for every node
mreach.closeness(A,M=2,cmode="all",large=FALSE)

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