Code and Data Repository for Social Network Prediction Problems: Using Meta-Paths and Dynamic Heterogeneous Graph Representation for Label Propagation

This work introduces a dynamic heterogeneous graph representation that integrates time into both nodes and edges, enabling a more accurate modeling of multiplex and evolving relationships in social networks. We further propose Meta-paths + LPA, an extension of the Label Propagation Algorithm that incorporates temporal meta-paths for improved classification on dynamic heterogeneous structures. The framework is demonstrated through a case study on Steemit, showcasing its ability to handle complex time-dependent queries and prediction tasks.