  We introduce a quantitative measure of network bipartivity as a proportion of
even to total number of closed walks in the network. Spectral graph theory is
used to quantify how close to bipartite a network is and the extent to which
individual nodes and edges contribute to the global network bipartivity. It is
shown that the bipartivity characterizes the network structure and can be
related to the efficiency of semantic or communication networks, trophic
interactions in food webs, construction principles in metabolic networks, or
communities in social networks.
