Extracting representative user subset of social networks towards user characteristics and topological features

摘要: Extracting a subset of representative users from the original set in social networks plays critical role Social Network Analysis. In existing studies, some researchers focus on preserving users’ characteristics when sampling users, while others pay attention to topology structure. However, both and network contain abundant information users. Thus, it is preserve them extracting user subset. To achieve goal, we propose novel approach this study, formulate problem as RUS (Representative User Subset) that proved an NP-Hard problem. solve problem, two approaches KS (K-Selected) optimized method (ACS) are consisted clustering algorithm model, where greedy heuristic proposed model. addition, pruning strategy by taking advantage MaxHeap validate performance approach, extensive experiments conducted real-world datasets. Results demonstrate our methods outperform state-of-the-art approaches.