Students’ emotional analysis on ideological and political teaching classes based on artificial intelligence and data mining

Abstract

Ideological and political teaching emotion is an important reflection of students’ learning achievements. At present, the effect of emotion analysis of ideological and political students is poor. This article builds on the artificial intelligence technology and combines machine learning data mining ideas to construct a student emotion analysis model in the ideological and political classroom. Starting from the individual, based on the individual’s own emotions and external stimuli, this article carries out emotion transfer probability statistics on the dialogues with emotions marked, and obtains the individual’s emotion transfer matrix. After the corresponding model is constructed, it can be applied to practice, and the research is conducted from the aspects of systematic emotion analysis effect and teaching promotion effect. In addition, this study designs a controlled experiment to analyze the effects of the model. The research results show that the model constructed in this paper has good performance.