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Nowadays, In the process of emotion analysis, the most commonly used feature method is based on the dictionary vector space model (VSM), latent semantic analysis (LSA) and word2vec which is based on unsupervised algorithm. All of the above models are applied in a single word. In this paper, having remarked the Douban datasets through the semantic role which was crawled on the internet, we making use of the result to traverse the order tree, and taking advantage of Modified Hidden Markov Model, and in the experiment the optimization function is cross entropy and the way that we find the best solution is stochastic gradient decline. In the end, we find LSTM model for test and verify the accuracy of the feature extraction, it turn out to be that this mean has a good effect on sentiment analysis.