Code and Data Repository for Social Network Prediction Problems: Using Meta-Paths and Dynamic Heterogeneous Graph Representation for Label Propagation
提出一种动态异构图表示方法，将时间维度融入节点和边，并扩展标签传播算法（Meta-paths + LPA）以处理动态异构结构，通过Steemit案例展示其处理复杂时间相关查询和预测任务的能力。
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.