Concerning that most Web video categorization researches just focus on the basic simple fusion of the information from text model and visual model, a Web video classification method based on the bidirectional propagation of heterogeneous attributes was proposed. Firstly, the method adopted K-means clustering to divide key frames into multiple clusters, and modeled videos at the level of frame. For each cluster, a part of key frames were randomly chosen to propagate their text information to the cluster. For each key frame, the text explanation of the corresponding cluster was transferred to this frame. Finally, the Web video was classified based on the extended text information from dual propagation by using Support Vector Machine (SVM) classifiers. The method integrates heterogeneous attributes well based on the dual propagation. The experimental results demonstrate the effectiveness of the method in the Web video classification.