Sentiment classification model for student teaching evaluation based on deep learning technology

In order to improve the effect of emotion classification of students’ teaching evaluation, this paper studies the emotion classification of students’ teaching evaluation combined with deep learning technology. This paper presents a sentiment analysis method based on the sentiment dictionary of teaching evaluation as a cold start solution when the marking data is insufficient. This method builds a collocation dictionary for teaching evaluation, solves the polar context-related problems of emotion words, introduces parallel relation and similarity calculation, and designs multi-level polarity recognition strategies for emotion words, so as to improve the performance of emotion analysis. The research shows that the classification model of student teaching evaluation based on deep learning proposed in this paper has a good effect on emotion classification, and has a certain effect on promoting interaction between teachers and students. © 2024 Inderscience Publishers. All rights reserved.