 This paper proposes two new algorithms, LPAWB plus and DIRT LPAWB plus, for identifying communities of nodes in bipartite networks. These algorithms are based on the idea of maximizing weighted modularity, which measures the extent to which nodes within a given community interact more with each other than they do with nodes outside their community. The algorithms were tested against Kwan by Moe, another algorithm designed to maximize weighted modularity, and both algorithms were shown to produce results comparable to those of Kwan by Moe. Additionally, DIRT LPAWB plus was able to identify higher quality partitions than Kwan by Moe, in some cases. The algorithms have the advantage of being faster than Kwan by Moe, making them suitable for large networks. This article was offered by Stephen J. Beckett.