  The bidirectional selection between two classes widely emerges in various
social lives, such as commercial trading and mate choosing. Until now, the
discussions on bidirectional selection in structured human society are quite
limited. We demonstrated theoretically that the rate of successfully matching
is affected greatly by individuals neighborhoods in social networks, regardless
of the type of networks. Furthermore, it is found that the high average degree
of networks contributes to increasing rates of successful matches. The matching
performance in different types of networks has been quantitatively
investigated, revealing that the small-world networks reinforces the matching
rate more than scale-free networks at given average degree. In addition, our
analysis is consistent with the modeling result, which provides the theoretical
understanding of underlying mechanisms of matching in complex networks.
