Daily Peer Relationships and Academic Achievement among College Students: A Social Network Analysis Based on Behavioral Big Data

Abstract

This study aimed to detect college students’ daily peer networks through a behavioral big-data-driven social network analysis and to explore the relationship between college students’ daily peer relationships and academic achievement. We collected data on the class attendance, eating, and bathing records of 4738 undergraduate students who entered a university in 2018 to infer the daily peer relationship networks of students. The Louvain algorithm and some network indicators such as density and average clustering coefficient were used to investigate social network characteristics of peer relationship networks. The findings show that initially, students in the same dormitory tended to form daily peer relationships, gradually shifting toward relationships centered on classmates as time progressed. These peer networks often aligned with geographical location and living areas. Moreover, the peers of college students who received high-level scholarships were more likely to receive scholarships. The number of peers was positively correlated with the likelihood of receiving a scholarship. The research findings contribute to the application of information technology to promote the sustainable development of higher education and individual students.