  Many real-world networks display a natural bipartite structure. Investigating
it based on the original structure is helpful to get deep understanding about
the networks. In this paper, some real-world bipartite networks are collected
and divided into two types, dependence bipartite networks and independence
bipartite networks, according to the different relation of two sets of nodes.
By analyzing them, the results show that the actors nodes have scale-free
property in the dependence networks, and there is no accordant degree
distribution in the independence networks for both two types of nodes. In order
to understand the scale-free property of actors in dependence networks, two
growing bipartite models without the preferential attachment principle are
proposed. The models show the scale-free phenomena in actors' degree
distribution. It also gives well qualitatively consistent behavior with the
empirical results.
