COMMUNITY DETECTION IN TRIPARTITE NETWORKS OF UNIVERSITY STUDENT MOBILITY FLOWS

The purpose of this study is to explore how the multimode network approach can be used to analyse network patterns derived from student mobility flows. We define a tripartite network based on a three-mode data structure, consisting of Italian provinces of residence, universities and fields of study, with student exchanges representing the links between them. A comparison of algorithms for detecting communities from tripartite networks based on modularity optimization is provided, revealing relevant information about the phenomenon under analysis over time. The findings are applied to a real dataset containing micro-level longitudinal information on Italian university students’ careers.