  Detecting communities in complex networks accurately is a prime challenge,
preceding further analyses of network characteristics and dynamics. Until now,
community detection took into account only positively valued links, while many
actual networks also feature negative links. We extend an existing Potts model
to incorporate negative links as well, resulting in a method similar to the
clustering of signed graphs, as dealt with in social balance theory, but more
general. To illustrate our method, we applied it to a network of international
alliances and disputes. Using data from 1993--2001, it turns out that the world
can be divided into six power blocs similar to Huntington's civilizations, with
some notable exceptions.
