Analysis and Application of College Students' Network Behavior Based on Data Mining

Wei Zhang, Wei Zhang, Ying-ying Gao, Thelma Palaoag

2024

Abstract

With the continuous development of information construction in universities, campus network has become the main channel for teachers and students to study, live and work. While the Internet brings convenience to teaching, it also has some negative effects. This paper collects one-year data of the university campus network server firstly, and adopts data mining technologies to complete the pre-processing of college students’ Internet data through massive data cleaning, label naming, clustering and transformation operations. Then the classification model of college students’ network behavior is constructed by user behavior classification algorithm and Pearson Product-Moment Correlation Coefficient is used for correlation analysis. Subsequently K-means algorithm is used to cluster data and machine learning method is used to match data patterns. Finally, the association rule mining algorithm is used to draw conclusions related to research objectives from students’ behavior data. The results show, except for the small use of campus network during winter and summer vacations, the average time spent on campus network in other months is more than 300 hours, and the average time spent online accounts for 41.67% of the total school time. The top three of college students’ concerned fields are social networking (25.65%), search (17.92%) and video (16.27%). And the top three types of Internet access for excellent students are learning (27.95%), video (18.51%) and social (13.44%). The analysis of results express that the network can improve college students’ academic performance, but it also negatively affects their studies. According to this study, university management departments can optimize and guide students to use the network appropriately, and to improve the informatization level of student management gradually.

Paper Citation

in Harvard Style

Zhang W., Gao Y. and Palaoag T. (2024). Analysis and Application of College Students' Network Behavior Based on Data Mining. In Proceedings of the 1st International Conference on Data Mining, E-Learning, and Information Systems - Volume 1: DMEIS; ISBN 978-989-758-715-3, SciTePress, pages 22-30. DOI: 10.5220/0012876000004536

in Bibtex Style

@conference{dmeis24,
author={Wei Zhang and Ying-ying Gao and Thelma Palaoag},
title={Analysis and Application of College Students' Network Behavior Based on Data Mining},
booktitle={Proceedings of the 1st International Conference on Data Mining, E-Learning, and Information Systems - Volume 1: DMEIS},
year={2024},
pages={22-30},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012876000004536},
isbn={978-989-758-715-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Mining, E-Learning, and Information Systems - Volume 1: DMEIS
TI - Analysis and Application of College Students' Network Behavior Based on Data Mining
SN - 978-989-758-715-3
AU - Zhang W.
AU - Gao Y.
AU - Palaoag T.
PY - 2024
SP - 22
EP - 30
DO - 10.5220/0012876000004536
PB - SciTePress