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Influence Maximization in Real-World Closed Social Networks

Summary: Addresses influence maximization in closed networks where seeds can recommend a few existing friends; problem shown NP-hard. Proposes an efficient iterative edge-augmentation that inserts a bounded number of original edges into the diffusion graph to boost spread, validated on real networks and a live deployment. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13037
Venue
VLDB
Year
2023
Pagerank
4.9677027e-05
Overall Rank
6,669 | 53.61%
DOI
10.14778/3565816.3565821

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