The invention discloses a text-enhancing network expression learning method, and relates to a complex network analysis technology. A new text-information-enhancing network expression learning method is put forward on the basis of non-negative matrix decomposition, and for the network structure, in combination with the first-order and second-order similarity between nodes, network expression is obtained through a decomposition similarity matrix; for the text clustering structure related to the nodes, decomposition is conducted on a text-lexical item matrix to obtain a text clustering affinity matrix, the consistency relationship is established between the network expression and the text clustering structure through the text clustering affinity matrix, and therefore network expression learning is controlled by the network structure and the text clustering structure related to the joints. By means of the method, the network structure is depicted, the text clustering structure related to the joints is also depicted, additional information beside the network structure is added to the network expression learning, the learned nodes are used for expressing more available information, and higher identifiability is achieved.