1. Degree Centrality Measures
setwd("D:/R_Labs")
data<- "sample_adjmatrix.csv"
el<-read.table(data, header=T, row.names=1, sep=",")
m=as.matrix(el)
gplot(m, displaylabels=TRUE)
![](data:image/png;base64,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)
sna::degree(m)
## [1] 6 8 2 8 4 10 2
sna::degree(m, cmode = "indegree")
## [1] 3 4 1 4 2 5 1
sna::degree(m,cmode="outdegree")
## [1] 3 4 1 4 2 5 1
# Calculate the degree of m using gapply
gapply(m,1,rep(1,7),sum)
## 23732 23778 23824 23871 58009 58098 58256
## 3 4 1 4 2 5 1
2. Basic Centrality Measures
Degree, Clonseness, Betweenness
Comparisons between Degree and Betweenness
dg<- sna::degree(m)
bt<- sna::betweenness(m)
plot(bt,dg, xlab="Betweenness Centrality", ylab="Degree Centrality", main = "Degree vs. Betweenness", col="red", pch=5)
![](data:image/png;base64,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)
gplot(m, vertex.cex=sqrt(dg) , displaylabels=TRUE)
![](data:image/png;base64,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)
gplot(m, vertex.cex=sqrt(bt)+1 , displaylabels=TRUE)
![](data:image/png;base64,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)
3. Create geodesic path count and geodesic distance matrix
geodist(m)
## $counts
## [,1] [,2] [,3] [,4] [,5] [,6] [,7]
## [1,] 1 1 1 1 2 1 1
## [2,] 1 1 1 1 2 1 1
## [3,] 1 1 1 1 2 1 1
## [4,] 1 1 1 1 1 1 1
## [5,] 2 2 2 1 1 1 1
## [6,] 1 1 1 1 1 1 1
## [7,] 1 1 1 1 1 1 1
##
## $gdist
## [,1] [,2] [,3] [,4] [,5] [,6] [,7]
## [1,] 0 1 2 1 2 1 2
## [2,] 1 0 1 1 2 1 2
## [3,] 2 1 0 2 3 2 3
## [4,] 1 1 2 0 1 1 2
## [5,] 2 2 3 1 0 1 2
## [6,] 1 1 2 1 1 0 1
## [7,] 2 2 3 2 2 1 0
$counts: a matrix containing the number of geodesics between each pair of vertices
$gdist: a matrix containing the geodesic distances between each pair of vertices