The Analytical System for Determining the Attitude of Students to the University

Introduction. In the context of the rapid development of higher education and growing competition between educational institutions, understanding students’ attitude towards the university becomes critical to improving the quality of educational services. Student feedback is a valuable source of information for assessing the effectiveness of the educational process, administrative services, and the general atmosphere at the university. However, traditional methods of collecting and analyzing feedback are often not automated, requiring significant time and human resources to process large amounts of text data. Existing software solutions use methods for processing and analyzing text tone based on machine learning methods and algorithms (naive Bayesian classifier, support vector machine, logistic regression), as well as deep learning (recurrent neural networks). At the same time, most of the available software solutions are not free, which makes it difficult to use them widely in universities, especially those with limited financial resources. Therefore, there is a need to develop new solutions that will not only be available for use, but also provide high accuracy and efficiency in processing text reviews. The purpose of the article. The article is aimed at developing an analytical system, its mathematical and software tools for determining students’ attitude towards the university based on their textual feedback. The developed system should provide high accuracy and efficiency in working with text data, automating the process of analyzing reviews and minimizing human resources for information processing. Results. A component model of the system for determining the attitude of students to the university was built. Student feedback from Telegram channels was collected. Sentiment analysis, statistical data analysis, time series analysis, and cluster analysis were conducted. The developed system allows to automatically receive a report on students’ attitude towards the university based on the proposed methods. The software implementation of the system in the Python programming language has been carried out. Keywords: analytical system, student feedback, system for determining students’ attitude towards the university, text tone analysis, statistical data analysis, time series analysis, cluster analysis.