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Dear Samin,

I recently wrote about a signed version of James Fowler's 108th senate  
co-sponsorship network in:

Neal, Z. (2014). The backbone of bipartite projections: Inferring  
relationships from co-authorship, co-sponsorship, co-attendance and  
other co-behaviors. Social Networks, 39, 84-97.

The network captures political alliances (positive ties) and  
antagonisms (negative ties) among 100 senators based on their bill  
co-sponsorship activities.  I've posted a copy of the network at  
http://www.msu.edu/~zpneal/108senate_signed.csv

This network is a bit bigger than what you're looking for.  But, the  
Stochastic Degree Sequence Model (SDSM) discussed in that paper can be  
used to infer signed networks from any bipartite data, many examples  
of which are available from the sites you've already checked.

Best,
Zachary

-- 
Zachary Neal, Assistant Professor
Michigan State University
Department of Psychology & Global Urban Studies Program
316 Physics Road, Rm 262
East Lansing, MI 48824
http://www.msu.edu/~zpneal
Twitter: @zpneal

http://www.routledge.com/books/details/9780415881425/
http://www.routledge.com/books/details/9780415997270/
http://www.youtube.com/watch?v=Az6Uy7p3kas


Quoting Samin Aref <[log in to unmask]>:

> *****  To join INSNA, visit http://www.insna.org  *****
>
> Dear Socneters,
>
> I work on theories of structural balance and look for data on signed
> networks of small sizes (up to 50 nodes).
>
> I have already looked at SNAP and UCINET and found the data for highland
> tribes. SNAP offers data for three large signed networks (Wikipedia,
> Slashdot, and Epinions) as well, but they do not fit to my research.
>
> Any data for small communities (directed/undirected) with positive and
> negative relationships would be highly appreciated.
>
> Kind regards,
>
> *Samin Aref*
> CompSci PhD candidate <https://www.cs.auckland.ac.nz/people/sare618>
> Centre for Mathematical Social Science <http://cmss.auckland.ac.nz/>
> University of Auckland
> <https://www.cs.auckland.ac.nz/people/sare618>
>
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