Construction of hot spot tracking model of university network public opinion based on text clustering
Yuxiang Zou · 2021 IEEE 5th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) · 2021
From the perspective of big data, internet public opinions in higher education institutions are informative, arbitrary, invisible and abrupt. Taking consideration of these features, this paper constructs a model to tracking network public opinion hot spots in higher education institutions. Adopting data processing ways including Chinese words segmentation and text clustering based on Single-Pass, this model consists three parts: data collection, data processing and data analysis. Through this method, this paper figures out important contents among a bulk of online public opinion topics in colleges and universities and determinate hot spot topics focused by campus students.