Analysis of college students' consumption behavior based on campus card data
Ligan Gong, Kun GU, Xinming MING, Ming Xu, Bin QIN · JOURNAL OF SHENZHEN UNIVERSITY SCIENCE AND ENGINEERING · 2020
In order to further improve the intelligent management level of universities, we use big data and data mining technology to analyze the data including a university's campus card consumption records. Firstly, through the preprocessing and feature engineering of the extracted data, we analyze students' consumption level, consumption habits and other laws. Then, we cluster students into different groups with different consumption behaviors, and analyze the consumption structure and consumption behavior characteristics for the different groups in depth. Finally, by constructing a student co-occurrence network, we study the social relationships of students and find the lonely persons. The experimental results show that our clustering algorithm can assist the accurate student aid work, and the construction of the student co-occurrence network can also provide a certain reference for the psychological counseling work.