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## Re: [igraph] Working with large networks and how to sample from a graph?

 From: Peter Flom Subject: Re: [igraph] Working with large networks and how to sample from a graph? Date: Wed, 4 Apr 2012 13:46:35 -0400

```Thanks

These big networks are hard! My past experience is with networks of a couple
hundred nodes, at most

Peter

Peter Flom
Peter Flom Consulting
http://www.statisticalanalysisconsulting.com/
http://www.IAmLearningDisabled.com

-----Original Message-----
On Behalf Of Gábor Csárdi
Sent: Wednesday, April 04, 2012 1:34 PM
To: Help for igraph users
Subject: Re: [igraph] Working with large networks and how to sample from a
graph?

On Wed, Apr 4, 2012 at 7:26 AM, Tamás Nepusz <address@hidden> wrote:
>> 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.
>
> Well, it depends on how you want to do it. You can try selecting 5000
nodes randomly from the entire network and then take the subgraph; this is
relatively simple:
>
> library(igraph)
> vs <- sample.int(vcount(g), 5000)-1
> g2 <- subgraph(g, vs)
>
> However, if your graph is large and sparse enough, there is a chance that
the resulting graph will not be connected at all, and then your estimates
will bear no resemblance at all to the "real" betweenness values.

Well, I'm not convinced that there is any kind of sampling that will tell
you much about betweenness values in the original network.
(Unless you network structure is special and you can use this fact in the
sampling.) I would recommend doing some simulations first, with
(say) snowball sampling.

Gabor

[...]
--
Gabor Csardi <address@hidden>     MTA KFKI RMKI

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