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weighted network centrality measures by network size
2 messages · Jenny Jiang, Suzen, Mehmet
1 day later
Hi Jenny, Have you tried igraph before? See, http://igraph.org/r/doc/ There are couple of centrality measures there. Best, -m
On 6 August 2014 02:50, Jenny Jiang <jiangyunbei at y7mail.com> wrote:
Dear R-help,
My name is Jenny Jiang and I am a Finance Honours research
student from the University of New South Wales Australia. Currently my
research project involves the calculating of some network centrality
measures in R, which are degree, closeness, betweenness and eigenvector. However I am having some issue regarding to the calculation of
the weighted centrality measures by network size. For example, currently
my code allows me to calculate centrality measures for each firm year,
and now I would like to calculate centrality measures weighted by the
firm network size for each firm year.
My current code is like the following:
install.packages("statnet")
library(statnet)
#read csv
data <- read.csv("D:\\Users\\z3377013\\Desktop\\networknew1.csv",header=TRUE)
#companies <- unique(data$CompanyID_)
#years <- unique(data$Year)
pairs <- unique(data[,c(1,3)])
#directors <- unique(c(data$DirectorID_,data$DirectorID_Connected))
#director_map <- 1:length(directors)
#names(director_map) <- c(as.character(directors))
#for (i in 1:nrow(data)) {
# data[i,2] = director_map[as.character(data[i,2])]
# data[i,4] = director_map[as.character(data[i,4])]
#}
sink("D:\\Users\\z3377013\\Desktop\\measure1.csv")
for (i in 1:nrow(pairs)) {
d <- subset(data, CompanyID_==pairs[i,1]&Year==pairs[i,2])
directors <- unique(c(d$DirectorID_,d$DirectorID_Connected))
director_map <- 1:length(directors)
names(director_map) <- c(as.character(directors))
for (j in 1:nrow(d)) {
d[j,2] = director_map[as.character(d[j,2])]
d[j,4] = director_map[as.character(d[j,4])]
}
net<-network(d[,c(2,4)],directed=F,loops=F,matrix.type="edgelist")
degree <- degree(net, cmode="freeman", gmode="graph")
closeness <- closeness(net,gmode="graph",cmode="undirected")
betweenness <- betweenness(net,gmode="graph",cmode="undirected")
evcent <- evcent(net,gmode="graph",use.eigen=TRUE)
write.csv(cbind(pairs[i,], directors, degree, closeness, betweenness, evcent), row.names=FALSE)
}
sink()
And an example of my data structure is like the following:
CompanyID_ DirectorID_ Year DirectorID_Connected
900 3700068021 2003 3699838021
900 3700418032 2003 3699838021
900 3700598032 2003 3699838021
900 3700898032 2003 3699838021
900 3703478063 2003 3699838021
900 3703628063 2003 3699838021
900 3703838063 2003 3699838021
900 3703998063 2003 3699838021
900 3699838021 2003 3700068021
900 3700418032 2003 3700068021
900 3700598032 2003 3700068021
900 3700898032 2003 3700068021
900 3703478063 2003 3700068021
900 3703628063 2003 3700068021
900 3703838063 2003 3700068021
900 3703998063 2003 3700068021
900 3699838021 2003 3700418032
900 3700068021 2003 3700418032
900 3700598032 2003 3700418032
900 3700068021 2004 3699838021
900 3700418032 2004 3699838021
900 3700598032 2004 3699838021
900 3700898032 2004 3699838021
900 3703478063 2004 3699838021
1290 1604538114 2003 427207466
1290 3556906472 2003 427207466
1290 3701108032 2003 427207466
1290 3708458104 2003 427207466
1290 3708478104 2003 427207466
1290 3711248135 2003 427207466
1290 10167110612 2003 427207466
1290 10271811383 2003 427207466
where for each firm-year I have a list of directors and their corresponding connected directors within that firm-year.
If you could
provide me the R code regarding to how to calculate the weighted measures by network size that that would be really
helpful.
I cannot be more than appreciated.
Best regards
Jenny
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