  This paper introduces a computationally inexpensive method of extracting the
backbone of one-mode networks projected from bipartite networks. We show that
the edge weights in the one-mode projections are distributed according to a
Poisson binomial distribution and that finding the expected weight distribution
of a one-mode network projected from a random bipartite network only requires
knowledge of the bipartite degree distributions. Being able to extract the
backbone of a projection is highly beneficial in filtering out redundant
information in large complex networks and narrowing down the information in the
one-mode projection to the most relevant. We demonstrate that the backbone of a
one-mode projection aids in the detection of communities.
