Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study
Summary: Benchmarks IM methods under identical conditions via a unified platform, enabling apples-to-apples comparisons. Finds deficiencies, debunks IM myths, and shows no universally dominant technique; performance depends on the metric. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Akhil Arora (Xerox Corporation)
- 2. Sainyam Galhotra (University of Massachusetts Amherst)
- 3. Sayan Ranu (Indian Institute of Technology Delhi)
BibTeX Citation
@inproceedings{arora_sigmod17,
title = {{Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study}},
author = {Arora, Akhil and Galhotra, Sainyam and Ranu, Sayan},
series = {{SIGMOD} '17},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3035981.3035924},
url = {https://dl.acm.org/doi/10.1145/3035981.3035924},
year = {2017}
}
Incoming Citations (Sorted by Pagerank)
Showing 17 of 17 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 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 |
| 296 | A Data-Based Approach to Social Influence Maximization | 2012 | VLDB | 0.00022220351 |
| 315 | Influence Maximization in Near-Linear Time: A Martingale Approach | 2015 | SIGMOD | 0.00021436156 |
| 453 | Stop-and-Stare: Optimal Sampling Algorithms for Viral Marketing in Billion-scale Networks | 2016 | SIGMOD | 0.00018145895 |
| 1,919 | Holistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models | 2016 | SIGMOD | 9.4850778e-05 |
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