Efficient Algorithms for Budgeted Influence Maximization on Massive Social Networks
Summary: Improves BIM approximation to 1 - 1/e_beta - epsilon (≈0.355) with reverse sampling on massive networks. Introduces bound-estimation and seed-selection techniques that reduce seed-set-size dependence, yielding large practical speedups over prior work. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Song Bian
- 2. Qintian Guo
- 3. Sibo Wang
- 4. Jeffrey Xu Yu
Incoming Citations (Sorted by Pagerank)
Showing 12 of 12 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 90 | A Data-Based Approach to Social Influence Maximization | 2012 | VLDB | 0.00052068982 |
| 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 |
| 436 | Stop-and-Stare: Optimal Sampling Algorithms for Viral Marketing in Billion-scale Networks | 2016 | SIGMOD | 0.00023259324 |
| 1,652 | Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study | 2017 | SIGMOD | 0.00011010086 |
| 1,801 | Online Processing Algorithms for Influence Maximization | 2018 | SIGMOD | 0.00010510943 |
| 2,220 | Holistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models | 2016 | SIGMOD | 9.2622402e-05 |
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