Re: [R] For Social Network Analysis-Graph Analysis - How to convert 2 mode data to 1 mode data?

From: Gabor Csardi <csardi_at_rmki.kfki.hu>
Date: Tue, 20 May 2008 09:08:28 +0200

Solomon, sorry for the delay. In igraph vertices are numbered from 0, so you need

keep <- 0:3

and then the function i've sent seems to work. But i can see that you also have a solution now.

Gabor

On Sat, May 17, 2008 at 09:32:27AM -0400, Messing, Solomon O. wrote:
> Consider the following two mode-data:
>
> edgelist:
> actor event
> 1 Sam a
> 2 Sam b
> 3 Sam c
> 4 Greg a
> 5 Tom b
> 6 Tom c
> 7 Tom d
> 8 Mary b
> 9 Mary d
>
> Two-Mode Adjacency Matrix:
> a b c d
> Sam 1 1 1 0
> Greg 1 0 0 0
> Tom 0 1 1 1
> Mary 0 1 0 1
>
> To transform two mode to one mode data, we need a function that transforms the
> data like so:
>
> Sam is connected to Greg (via event a)
> Sam is connected to Tom (via event b and c)
> Sam is connected to Mary (via event b)
> Tom is connected to Mary (via event b and d)
>
> OK, now I load my data by executing the following:
> ###############################################################################
> ####
> require(igraph)
> df <- data.frame(actor = c
> ('Sam','Sam','Sam','Greg','Tom','Tom','Tom','Mary','Mary'),
> event =c('a','b','c','a','b','c','d','b','d') )
> g = graph.data.frame(df, directed=F) #Coerce data to igraph object 'g'
>
> #Loading Function two.to.one:
> ##two.to.one() transforms 2-mode data to 1-mode
> two.to.one <- function(g, keep) {
> neis <- neighborhood(g, order=2)
> neis <- lapply(seq(neis), function(x) neis[[x]][ neis[[x]] != x-1]) ## drop
> self-loops
> neis <- lapply(neis, function(x) x[ x %in% keep ]) ## keep
> only these
> neis <- lapply(seq(neis), function(x) t(cbind(x-1, neis[[x]]))) ## create
> edge lists
> neis[-keep-1] <- NULL ## these
> are not needed
> neis <- matrix(unlist(neis), byrow=TRUE, nc=2) ## a
> single edge list
> neis <- neis[ neis[,1] > neis[,2], ] ## count
> an edge once only
> mode(neis) <- "character"
> g2 <- graph.edgelist(neis, dir=FALSE)
> V(g2)$id <- V(g2)$name ## 'id' is used in Pajek
> g2
> }
>
> #Actors are the first 4 verticies, set them to be kept:
> keep = V(g)[1:4]
> #Convert matrix with two.to.one:
> g2 = two.to.one(g, keep)
> g2
> ###############################################################################
> ####
> This yields the following output:
> > g2
> Vertices: 4
> Edges: 2
> Directed: FALSE
> Edges:
>
> [0] 3 -- 2
> [1] 4 -- 1
>
> But, this can't be right. Here there are only two edges where there should be
> four, and if I am inturpreting correctly, the output it is reporting that Tom
> is connected to Greg (he is not) and Sam is connected to Mary (which is true).
>
> When I load my function, which is designed to transform a two mode edgelist
> (e.g. two columns of data) into a one-mode adjacency matrix it seems to work:
> ###############################################################################
> ####
> #load my function
> df.to.nxn <- function( x, y )
> { # x values will be the N
> x N values
> M <- matrix( nrow = length( unique( x ) ), ncol = length( unique( x ) ),
> dimnames = list( unique( x ), unique( x ) ) )
> M[ 1:length( unique( x ) ), 1:length( unique( x ) ) ] <-
> 0 #initialize the values to 0 - this possibly could be
> removed for illustrative purposes
> for( i in 1:length( x ) )
> { # iterate through rows of
> data
> index = which( y == y[i] )
> M[ as.character( x[ index ] ), as.character( x[ index ] ) ] =
> 1
> }
> M
> # return M, an N x N matrix
> }
> #Convert matrix
> g3 = df.to.nxn(df$actor, df$event)
> g4 = graph.adjacency(g3, mode = "undirected", diag = F)
> V(g4)$name = row.names(g3)
> g4
> ###############################################################################
> ####
> This yields:
> > g4
> Vertices: 4
> Edges: 4
> Directed: FALSE
> Edges:
>
> [0] Sam -- Greg
> [1] Sam -- Tom
> [2] Sam -- Mary
> [3] Tom -- Mary
>
> Which is what we wanted. I have not figured out how to weight edges yet (the
> Sam and Tom edge and the Tom and Mary edge should perhaps be weighted at 2
> because 'connected twice' -- connected by two events).
>
> -Solomon
>
> ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
> From: Gabor Csardi [mailto:csardi_at_rmki.kfki.hu]
> Sent: Wed 5/14/2008 4:01 AM
> To: Messing, Solomon O.
> Cc: R Help list
> Subject: Re: [R] For Social Network Analysis-Graph Analysis - How to convert 2
> mode data to 1 mode data?
>

>
> Please stay on the list.

>
> On Tue, May 13, 2008 at 06:05:15PM -0400, Messing, Solomon O. wrote:
> > Gabor,
> >
> > By the way, this seems to work:

>
> I'm a bit lost. So now you're converting your data frame
> to a matrix? Why? Or you're doing the two-mode to one-mode
> conversion here? It does not seem so to me.

>
> Btw. there is a get.adjacency function in igraph to convert
> a graph to an adjacency matrix.

>
> G.
>
> >
> > df.to.nxn <- function( x, y ){
> > # x values will be the N x N values
> > M <- matrix( nrow = length( unique( x ) ), ncol = length( unique( x
> > ) ),
> > dimnames = list( unique( x ), unique( x ) ) )
> > M[ 1:length( unique( x ) ), 1:length( unique( x ) ) ] <- 0
> > # initialize the values to 0
> > for( i in 1:length( x ) ) {
> > # iterate through rows of data
> > index = which( y == y[i] )
> > M[ as.character( x[ index ] ), as.character( x[ index ]
> > ) ] = 1
> > }
> > M
> > # return M, an N x N matrix
> > }
>
> --
> Csardi Gabor <csardi_at_rmki.kfki.hu> UNIL DGM
>

-- 
Csardi Gabor <csardi_at_rmki.kfki.hu>    UNIL DGM

______________________________________________
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.
Received on Tue 20 May 2008 - 07:22:50 GMT

Archive maintained by Robert King, hosted by the discipline of statistics at the University of Newcastle, Australia.
Archive generated by hypermail 2.2.0, at Mon 26 May 2008 - 19:30:43 GMT.

Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help. Please read the posting guide before posting to the list.

list of date sections of archive