Analysis of the Sentiment in the Evaluation Texts of University Students by Means of the Concept of Flexible Management

Abstract

With the development of information technology (IT) and the popularity of the Internet, it is easier to obtain college students’ teaching evaluation text data. However, it is still challenging to deeply understand and effectively analyze these texts. Based on the flexible management concept in universities, this study aimed to understand and analyze the teaching evaluation texts of college students more accurately, thereby improving the teaching quality. The implicit features of those texts were recognized first in this study, which aimed to supplement and improve the implicit features neglected by existing sentiment analysis methods. A sentiment analysis method based on Bidirectional Encoder Representations from Transformers (BERT) was adopted to explore the deep semantic information of texts. It was done by using deep learning technology and to improve the accuracy of sentiment analysis. This in turn provides more valuable reference information for university teaching management and further promotes the practical application of the flexible management concept in university teaching management.