Analysis of Student Social Relationships Based on Three-Dimensional Spatio-Temporal Co-occurrence

This research proposes a method for analyzing student social relationships based on three-dimensional spatio-temporal co-occurrence. By leveraging detailed timestamp information from student behavior data, the method constructs a three-dimensional co-occurrence tensor encompassing location, date, and time dimensions. Two key features, three-dimensional co-occurrence spatio-temporal diversity and weighted co-occurrence frequency, are extracted from this tensor. A multiple linear regression algorithm is then employed to calculate the social intensity values among students. Additionally, the Louvain community detection algorithm is utilized to mine hierarchical community social relationships from the constructed student social network.