Fine-grained analysis of emotion is a branch of sentiment analysis, with the expansion of social network, the division of simple positive or negative coarse-grained sentiment analysis cannot satisfy the need of practical application. Thus the fine-grained emotional analysis based on evaluation objects and their attributes has received attention in recent years. The successful application of deep learning in the field of natural language processing in recent years provides a new idea for the fine-grained analysis of emotion. Take NLPCC2013 task 2 Weibo data set as the research object, explore the classification results of microtext in different neural network structures and add word vectors for optimization. Finally, the influencing factors and development direction of finer-grained emotion analysis of neural network micro-blog essay are analyzed and summarized.