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 |
|---|---|---|---|---|
| 7,918 | Triangular Stability Maximization by Influence Spread over Social Networks | 2023 | VLDB | 5.4252033e-05 |
| 8,503 | Efficient Influence Minimization via Node Blocking | 2024 | VLDB | 5.3276429e-05 |
| 9,250 | Shortest Paths Discovery in Uncertain Networks via Transfer Learning | 2023 | SIGMOD | 5.2032182e-05 |
| 9,424 | Managing Conflicting Interests of Stakeholders in Influencer Marketing | 2023 | SIGMOD | 5.1779852e-05 |
| 9,969 | Fast and Space-Efficient Parallel Algorithms for Influence Maximization | 2024 | VLDB | 5.1014161e-05 |
| 11,067 | Augmenting Social Influence of Uncertain Seeds via Probabilistic Link Insertion | 2026 | VLDB | 4.9769913e-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 |
|---|---|---|---|---|
| 199 | Influence Maximization: Near-Optimal Time Complexity Meets Practical Efficiency | 2014 | SIGMOD | 0.00025510476 |
| 320 | Influence Maximization in Near-Linear Time: A Martingale Approach | 2015 | SIGMOD | 0.00021133139 |
| 1,965 | Holistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models | 2016 | SIGMOD | 9.3015421e-05 |
| 2,698 | Efficient Algorithms for Budgeted Influence Maximization on Massive Social Networks | 2020 | VLDB | 8.1163992e-05 |
| 4,055 | Real-Time Influence Maximization on Dynamic Social Streams | 2017 | VLDB | 6.8241743e-05 |
| 4,655 | Efficient Algorithms for Adaptive Influence Maximization | 2018 | VLDB | 6.482094e-05 |
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|---|---|---|---|---|
| 1 | 4,821 | Efficient Location-Aware Influence Maximization | 2014 | SIGMOD |
| 2 | 2,698 | Efficient Algorithms for Budgeted Influence Maximization on Massive Social Networks | 2020 | VLDB |
| 3 | 4,055 | Real-Time Influence Maximization on Dynamic Social Streams | 2017 | VLDB |
| 4 | 4,655 | Efficient Algorithms for Adaptive Influence Maximization | 2018 | VLDB |
| 5 | 8,134 | Coarsening Massive Influence Networks for Scalable Diffusion Analysis | 2017 | SIGMOD |
| 6 | 2,309 | Online Topic-Aware Influence Maximization | 2015 | VLDB |
| 7 | 8,765 | Maximizing Social Welfare in a Competitive Diffusion Model | 2021 | VLDB |
| 8 | 8,967 | Finding Seeds and Relevant Tags Jointly: For Targeted Influence Maximization in Social Networks | 2018 | SIGMOD |
| 9 | 299 | A Data-Based Approach to Social Influence Maximization | 2012 | VLDB |
| 10 | 2,588 | From Competition to Complementarity: Comparative Influence Diffusion and Maximization | 2016 | VLDB |