The invention discloses a subjective text emotion analysis method based on deep learning. The method includes the steps that 1, a C&W-SP model is established based on a C&W model, an emotion label and a word class label of a sentence are labeled in the sentence, a training set of a C&W_SPC&W-SP model is established, a C&W_SP model is trained through the training set, a word vector of each word in the training set is obtained, and a word vector file is formed; 2, a sentence vector set is established through an LSTM model according to the obtained word vector file; 3, a neutral network model is trained through the sentence vector set, and an emotion classification model is obtained; 4, the tested comment sentence is preprocessed, the tested sentence vectors are input in the emotion classification model, and the emotion tendency of the section of comment is obtained through calculation. According to the method, emotion tendency information and word class information are added into words, and the accuracy of emotion analysis is improved.