Good morning
My second post (and I certainly hope this one isn’t due to a typo!)
I have a large network (about 400,000 nodes and 4 million links). Visualizing
this is a problem. There isn't room on any reasonable page to print that sort
of network. Estimating betweenness measures on such a large graph is very time
consuming (even with the estimates, even with relatively low cutoff - and I am
not sure how a cutoff of 2 would affect things)
One idea I had was to take a small random sample from the network (say 5,000
nodes) but I am not sure exactly how to do this in igraph. Right now, I create
the graph thus:
<<<
library(igraph)
g <- graph.empty()
g <- add.vertices(g, nrow(traits),
MORE TRAITS
names <- V(g)$ISBN
ids <- 1:length(names)-1
names(ids) <- names
from <- as.character(links[,1])
to <- as.character(links[,2])
edges <- matrix(c(ids[from], ids[to]), nc=2)
g <- add.edges(g, t(edges))
>>>
Should I sample from the vertices prior to this construction? Or afterwards?
Also, any references on working with large graphs would be appreciated. My
prior experience is with much smaller graphs
Thanks!
Peter
Peter Flom
Peter Flom Consulting
http://www.statisticalanalysisconsulting.com/
http://www.IAmLearningDisabled.com
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