Abstract: The identification of communities is significant for the understanding of network structures and functions. In this study, we propose a framework to address the problem of community detection in bipartite networks based on principal components analysis. We apply the algorithm to real-world network data, showing that the algorithm successfully finds meaningful community structures of bipartite networks.