Friend Relation Recognization Algorithm Based on The Campus Card Consumption

Abstract

College students live alone without their parents and bear the influence of academics, life, personality, family, and other factors alone, which leads to the phenomenon of isolation and autism in some students. If this situation is not detected and resolved in time, it may cause serious consequences. This paper uses the consumption data of students to analyze the students' friendship situation. First, it examines the consumption data of the students' campus all-in-one cards and observes the consumption behaviors of the students from the three aspects of consumption time, consumption location, and consumption frequency. It is found that the more overlapping the trajectories of the consumption locations among students, the more likely there is a friendship between students. On this basis, this paper proposes a student friend discovery model, which further explores the social relationship between students from the perspective of multiple colleges, and can find both friend relationships and lonely students. The experimental results show that the excavated social relationships align with the actual situation.