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 (Royal Melbourne Institute of Technology)
- 2. Wenqing Lin (Tencent)
- 3. Zhifeng Bao (Royal Melbourne Institute of Technology)
- 4. Jiachen Sun (Tencent)
BibTeX Citation
@article{huang_vldb23,
title = {{Influence Maximization in Real-World Closed Social Networks}},
author = {Huang, Shixun and Lin, Wenqing and Bao, Zhifeng and Sun, Jiachen},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {2},
pages = {180--192},
doi = {10.14778/3565816.3565821},
url = {https://doi.org/10.14778/3565816.3565821},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,771 | Triangular Stability Maximization by Influence Spread over Social Networks | 2023 | VLDB | 5.5470467e-05 |
| 9,057 | Efficient Influence Minimization via Node Blocking | 2024 | VLDB | 5.3251649e-05 |
| 9,062 | Shortest Paths Discovery in Uncertain Networks via Transfer Learning | 2023 | SIGMOD | 5.3251649e-05 |
| 9,242 | Managing Conflicting Interests of Stakeholders in Influencer Marketing | 2023 | SIGMOD | 5.2993405e-05 |
| 10,611 | Augmenting Social Influence of Uncertain Seeds via Probabilistic Link Insertion | 2026 | VLDB | 5.093636e-05 |
| 11,286 | Fast and Space-Efficient Parallel Algorithms for Influence Maximization | 2024 | VLDB | 5.093636e-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 |
|---|---|---|---|---|
| 194 | Influence Maximization: Near-Optimal Time Complexity Meets Practical Efficiency | 2014 | SIGMOD | 0.000259047 |
| 315 | Influence Maximization in Near-Linear Time: A Martingale Approach | 2015 | SIGMOD | 0.00021436156 |
| 1,919 | Holistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models | 2016 | SIGMOD | 9.4850778e-05 |
| 2,752 | Efficient Algorithms for Budgeted Influence Maximization on Massive Social Networks | 2020 | VLDB | 8.1648436e-05 |
| 3,989 | Real-Time Influence Maximization on Dynamic Social Streams | 2017 | VLDB | 6.9716774e-05 |
| 4,804 | Efficient Algorithms for Adaptive Influence Maximization | 2018 | VLDB | 6.5010703e-05 |
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| 1 | 4,725 | Efficient Location-Aware Influence Maximization | 2014 | SIGMOD |
| 2 | 2,752 | Efficient Algorithms for Budgeted Influence Maximization on Massive Social Networks | 2020 | VLDB |
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