The message board text put forward by netizens on a certain issue is a suggestion or opinion, which is sparse and emotional. The traditional LDA model cannot solve the sparsity problem of the short message and ignores the emotional factor. In order to solve the above problems, a message board information extraction method based on LDA model and RNN model is proposed. First, eigenvalues are introduced to classify the text to solve the sparsity problem based on LDA model. Second, RNN model is

more »

... to realize the emotional features on the basis of message text vectorization. The experiment shows that the LDA model with eigenvalues has better topic extraction ability compared with the traditional model, and with the fusion of the RNN model, it can comprehensively display the potential information of the message text. As a result, the proposed method achieves information extraction maximize.