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Simone, I like your idea! BTW there is already an sna tag at stackoverflow:

http://stackoverflow.com/questions/tagged/sna

Another similar suggestion might be to create a "collective" github
repository for SNA or at least to compile all existing github
repositories with sna resources.

Furthermore, I was thinking that it would be magnificent if
computational socialnetworkers were apt to use the ipython notebook.
Notice that now Jupyter is already integrated with R:

https://tmp33.tmpnb.org/user/ALDwvf9OT7JN/notebooks/Welcome%20R%20%20-%20demo.ipynb

and rmagic is another option for R users who want to move in (i)python:

http://ipython.org/ipython-doc/1/config/extensions/rmagic.html

On Fri, Jul 10, 2015 at 10:38 AM, Simone Gabbriellini
<[log in to unmask]> wrote:
> great question/answers, if only we had a StackOverflow for SNA... :)
>
> 2015-07-10 7:05 GMT+02:00 Moses Boudourides <[log in to unmask]>:
>>
>> *****  To join INSNA, visit http://www.insna.org  *****
>>
>> Yes, Dmitry, this might be the case for huge networks. In that case I
>> would do what you were doing. Thank you.
>>
>> On Fri, Jul 10, 2015 at 8:01 AM, Dmitry Zinoviev <[log in to unmask]>
>> wrote:
>> > Moses,
>> >
>> > With all my respect, it's the line 2 of your snippet that may not work -
>> > exactly because the network is huge. One shall use a CSV reader or
>> > simply
>> > read the CSV edge list line by line or block by block and filter out the
>> > edges that are not in the subset. Assuming that the edges are stored as
>> > two
>> > columns of nodes and the CSV file has no header, the following snippet
>> > shall
>> > work:
>> >
>> > csvIn = open ("HugeFile.csv")
>> > csvOut = open ("Subset.csv", "w")
>> >
>> > line = csvIn.readline ()
>> > while line:
>> >     node1, node2 = line.strip().split(",")
>> >     if node1 in NodesSmall and node2 in NodesSmall:
>> >         csvOut.write (line)
>> >     line = csvIn.readline ()
>> >
>> > csvOut.close ()
>> >
>> > For the sake of performance, the list of nodes in the subset shall be
>> > converted to a dictionary:
>> > NodesSmall = dict ((node, node) for node in Gsmall.nodes())
>> >
>> > Hope it helps.
>> >
>> > On Fri, Jul 10, 2015 at 12:54 AM, Moses Boudourides
>> > <[log in to unmask]> wrote:
>> >>
>> >> *****  To join INSNA, visit http://www.insna.org  *****
>> >>
>> >> Absolutely I would back Dmitry in suggesting the use of Python in
>> >> order to merge networks as far as one avoids to use the relabelling
>> >> mapping employed in NetworkX (it's very problematic, I believe it has
>> >> to be rewritten). However, this is not the case here and so what I
>> >> would do is something like the following:
>> >>
>> >> import networkx as nx
>> >> Ghuge = nx.read_graphml("HugeNetwork.graphml")
>> >> Gsmall = nx.read_graphml("SubsetNetwork.graphml")
>> >> NodesSmall = Gsmall.nodes()
>> >> G = Ghuge.subgraph(NodesSmall)
>> >> attributesDictionary = Gsmall.nodes(data=True)
>> >> nx.set_node_attributes(G, 'attribute', attributesDictionary)
>> >
>> > --
>> > Dmitry Zinoviev
>> > Professor of Computer Science
>> > Suffolk University, Boston, MA 02114
>>
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>
>
>
>
> --
> Simone Gabbriellini, PhD
>
> PostDoc@DISI, University of Bologna
> mobile: +39 340 39 75 626
> email: [log in to unmask]
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>
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