  We study the community structure of networks representing voting on
resolutions in the United Nations General Assembly. We construct networks from
the voting records of the separate annual sessions between 1946 and 2008 in
three different ways: (1) by considering voting similarities as weighted
unipartite networks; (2) by considering voting similarities as weighted, signed
unipartite networks; and (3) by examining signed bipartite networks in which
countries are connected to resolutions. For each formulation, we detect
communities by optimizing network modularity using an appropriate null model.
We compare and contrast the results that we obtain for these three different
network representations. In so doing, we illustrate the need to consider
multiple resolution parameters and explore the effectiveness of each network
representation for identifying voting groups amidst the large amount of
agreement typical in General Assembly votes.
