Research on the evolutionary characteristics of hot topics in online public opinion of Chinese universities based on Weibo texts

Investigating the evolutionary characteristics of hot topics in the online public opinion of Chinese universities contributes to the identification and prediction of trends in university-related public opinion, offering valuable insights for the management of public discourse. This study collected and processed hot search data related to universities from Weibo between 2020 and 2024. The data were analyzed for topic discovery and sentiment using the LDA and BERT models. The evolutionary characteristics of these hot topics were then examined through data visualization. The results revealed that, over the past 5 years, the main topics in online public opinion related to Chinese universities fell into seven categories: Female faculty and students, Graduation and employment, Campus management and security, Education and teaching, Illegal activities and violations, Campus life, and Examination and enrollment. The evolution of these topics displayed distinct patterns: cyclical fluctuations in both the quantity and sentiment of education-related public opinion, the generation of topics driven by unforeseen events, shifts in hot topics influenced by educational values, and the polarization of sentiment surrounding these topics driven by online debates. This paper presents a research methodology for studying the evolution of university public opinion topics and provides a reference for understanding and managing public opinion in Chinese universities.