Application Analysis of Emotional Learning Model Based on Improved Text in Campus Review and Student Public Opinion Management

Abstract

In an era of rapid mobile Internet development, students are increasingly expressing their views on specific events through campus comments. In the Web 2.0 era, the concept of public media participation is widely used by students, and it is important to effectively analyze online campus public opinion comments and present the findings in a rationalized form for the management of campus public opinion. In the new era of education governance modernization, the level of public opinion management in universities has become a key indicator to improve the standard of education management in higher education institutions; therefore, this paper focuses on proposing an innovative deep learning-based research method for topic management of university public opinion. Firstly, through the improved LDA module with sentiment discrimination learning capability, the sentiment of the main arguments in the campus commentary is extracted, and then the statistical sentiment intensity of the in-depth learning module is used to analyze the sentiment intensity of the thematic arguments of different events in time series, so as to achieve the long-term tracking of the trend of the sentiment intensity of the whole event.