[R] weighted network centrality measures by network size

[Suzen, Mehmet]

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
>
>         [[alternative HTML version deleted]]
>
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>