For a given network, some nodes have been labeled into several groups (e.g., good/bad). It would then be of interest to label the rest of the nodes, based on the network information and partially labeled nodes. In this paper, we propose a semi-supervised learning method, by using so-called information prorogation. The method has very good performance in many settings, and is particularly effective in handling unbalanced and/or sparse network.