Research on Emotion Analysis and Psychoanalysis Application With Convolutional Neural Network and Bidirectional Long Short-Term Memory - Liu, Baitao (Frontiers in Psychology, 2022)
Abstract This paper mainly studies the emotion analysis method in the application of psychoanalysis based on sentiment recognition. The method is applied to the sentiment recognition module in the server, and the sentiment recognition function is effectively realized through the improved Convolutional Neural Network and Bi-Directional Long Short-Term Memory (C-BiL) model. Firstly, the implementation difficulties of C-BiL model and specific sentiment classification design are described. Then, the specific design process of C-BiL model is introduced, and the innovation of C-BiL model is indicated. Finally, the experimental results of the models are compared and analyzed. Among the deep learning models, the accuracy of C-BiL model designed in this paper is relatively high no matter in the binary classification, the three classification or the five classification, with an average improvement of 2.47% in Diary data set, 2.16% in Weibo data set and 2.08% in Fudan data set. Therefore, the C-BiL model designed in this paper can not only successfully classify texts, but also effectively improve the accuracy of text sentiment recognition.