Incremental Graph Computation: Anchored Vertex Tracking in Dynamic Social Networks

User engagement has recently received significant attention in understanding the decay and expansion of communities many online social networking platforms. When a user chooses to leave platform, it may cause cascading dropping out among her friends. In scenarios, would be good idea persuade critical users stay active network prevent such cascade because can have influence on whole network. Many studies been conducted find set (anchored) static However, networks are highly dynamic their structures continuously evolving. order fully utilize power anchored evolving networks, existing mine multiple sets at different times, which incurs an expensive computational cost. To better understand network, we target new research problem called Anchored Vertex Tracking (AVT) this paper, aiming track each timestamp networks. Nonetheless, is nontrivial handle AVT proved NP-hard. address challenge, develop greedy algorithm inspired by previous $k$-core study Furthermore, design incremental efficiently solve utilizing smoothness structure's evolution. The extensive experiments real synthetic datasets demonstrate performance our proposed algorithms effectiveness solving problem.