We present HAMLET, a suite of principles, scoring models and algorithms to automatically propagate metadata along edges in a document neighborhood. As a showcase scenario we consider tag prediction in community-based Web 2.0 tagging applications. Experiments using real-world data demonstrate the viability of our approach in large-scale environments where tags are scarce. To the best of our knowledge, HAMLET is the first system to promote an efficient and precise reuse of shared metadata in highly dynamic, large-scale Web 2.0 tagging systems.