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)
Incoming Non-self Citations Over Time
Authors
- 1. Shixun Huang
- 2. Wenqing Lin
- 3. Zhifeng Bao
- 4. Jiachen Sun
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,798 | Triangular Stability Maximization by Influence Spread over Social Networks | 2023 | VLDB | 4.6482149e-05 |
| 8,903 | Efficient Influence Minimization via Node Blocking | 2024 | VLDB | 4.427232e-05 |
| 8,907 | Shortest Paths Discovery in Uncertain Networks via Transfer Learning | 2023 | SIGMOD | 4.427232e-05 |
| 9,097 | Managing Conflicting Interests of Stakeholders in Influencer Marketing | 2023 | SIGMOD | 4.3967784e-05 |
| 10,313 | Augmenting Social Influence of Uncertain Seeds via Probabilistic Link Insertion | 2026 | VLDB | 4.1945683e-05 |
| 11,080 | Fast and Space-Efficient Parallel Algorithms for Influence Maximization | 2024 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 180 | Influence Maximization: Near-Optimal Time Complexity Meets Practical Efficiency | 2014 | SIGMOD | 0.00037135181 |
| 337 | Influence Maximization in Near-Linear Time: A Martingale Approach | 2015 | SIGMOD | 0.00027011645 |
| 2,220 | Holistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models | 2016 | SIGMOD | 9.2622402e-05 |
| 2,486 | Efficient Algorithms for Budgeted Influence Maximization on Massive Social Networks | 2020 | VLDB | 8.6741469e-05 |
| 4,371 | Real-Time Influence Maximization on Dynamic Social Streams | 2017 | VLDB | 6.2459569e-05 |
| 5,090 | Efficient Algorithms for Adaptive Influence Maximization | 2018 | VLDB | 5.7042676e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,078 | Efficient Location-Aware Influence Maximization | 2014 | SIGMOD | 5.715243e-05 |
| 2,486 | Efficient Algorithms for Budgeted Influence Maximization on Massive Social Networks | 2020 | VLDB | 8.6741469e-05 |
| 4,371 | Real-Time Influence Maximization on Dynamic Social Streams | 2017 | VLDB | 6.2459569e-05 |
| 5,090 | Efficient Algorithms for Adaptive Influence Maximization | 2018 | VLDB | 5.7042676e-05 |
| 7,904 | Coarsening Massive Influence Networks for Scalable Diffusion Analysis | 2017 | SIGMOD | 4.6214923e-05 |
| 8,591 | Maximizing Social Welfare in a Competitive Diffusion Model | 2021 | VLDB | 4.4896282e-05 |
| 2,490 | Online Topic-Aware Influence Maximization | 2015 | VLDB | 8.6584707e-05 |
| 8,628 | Finding Seeds and Relevant Tags Jointly: For Targeted Influence Maximization in Social Networks | 2018 | SIGMOD | 4.4817474e-05 |
| 90 | A Data-Based Approach to Social Influence Maximization | 2012 | VLDB | 0.00052068982 |
| 2,371 | From Competition to Complementarity: Comparative Influence Diffusion and Maximization | 2016 | VLDB | 8.9482922e-05 |