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Hi Ian,

I can show you code for igraph -- would need to think about it a bit more in statnet, but the principles are the same. Not elegant, no doubt, but it works. There may, for example, be a simpler way to do this with a merge of some sort. I just did this on a graph I had handy. I colored the names according to communities (found using the spinglass.community algorithm) using the colorspace package.

Given a graph g (370 vertices, 1565 edges):

spc <- spinglass.community(g, spins=20)
cols <- rainbow_hcl(10, c = c(80, 30), l = c(30, 90)) ## colorspace
g.layout <- layout.fruchterman.reingold(g)

ccc <- sort(betweenness(g), decreasing = TRUE)

thebigs <- names(ccc[1:20])
bignames <- rep(NA,370)
aaa <- rep(NA, 20)
for(i in 1:20) aaa[i] <- which(thebigs[i] == V(g)$name)
bignames[aaa] <- thebigs
V(g)$bignames <- bignames

plot(g, vertex.label=V(g)$bignames, layout=g.layout,
     vertex.size=0, vertex.color="white", vertex.frame.color="white",
     vertex.label.cex=0.75, vertex.label.color=cols[spc$membership], edge.color=rgb(209,209,209,70, max=255), edge.width=2)

You can alter the vertex label size, for example passing a vector argument to the vertex.label.cex argument.

Hope this helps.

Cheers,
Jamie
--
James Holland Jones
Associate Professor of Anthropology &
Senior Fellow, Woods Institute for the Environment

450 Serra Mall
Building 50
Stanford, CA 94305-2034

phone:	650-721-2484
fax:	650-725-0605
email:	[log in to unmask]
url:	http://www.stanford.edu/~jhj1




> On Aug 23, 2015, at 4:33 PM, Ian McCulloh <[log in to unmask]> wrote:
> 
> ***** To join INSNA, visit http://www.insna.org *****
> Hello!
> 
> I'm doing an SNA project on an organization of about 120 nodes.  I am using Statnet in R.  I want to make an SNA visualization where I only visualize the labels for the most central 10 or 20 nodes.  Does anyone have some R code that does this?
> 
> For context and example, here is code I have that will allow me to scale the node label based on centrality, and I can color the edges gray for contrast.
> 
> gplot(gn, label.cex=node.scale(node.scale(betweenness(gn))), label.col=1, label=network.vertex.names(gn), vertex.col=2, edge.col=8, vertex.cex=0.5)
> 
> I'd also be interested in iGraph implementation, but I'm using statnet for this project.
> 
> Kind Regards,
> 
> Ian
> 
> 
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