Maximizing Welfare in Social Networks under A Utility Driven Influence Diffusion model
Summary: UIC model links utility-driven adoption with influence diffusion for complementary items. Greedy allocation achieves (1-1/e-ε) welfare despite non-submodular objective; bundleGRD scales and outperforms baselines on real and synthetic networks. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Prithu Banerjee (University of British Columbia)
- 2. Wei Chen (Microsoft)
- 3. Laks V.S. Lakshmanan (University of British Columbia)
BibTeX Citation
@inproceedings{banerjee_sigmod19,
title = {{Maximizing Welfare in Social Networks under A Utility Driven Influence Diffusion model}},
author = {Banerjee, Prithu and Chen, Wei and Lakshmanan, Laks V.S.},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3319879},
url = {https://dl.acm.org/doi/10.1145/3299869.3319879},
year = {2019}
}
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,342 | CHASSIS: Conformity Meets Online Information Diffusion | 2020 | SIGMOD | 5.8092399e-05 |
| 6,526 | CompressGraph: Efficient Parallel Graph Analytics with Rule-Based Compression | 2023 | SIGMOD | 5.7559739e-05 |
| 7,971 | Minimizing the Regret of an Influence Provider | 2021 | SIGMOD | 5.4150644e-05 |
| 8,757 | Maximizing Social Welfare in a Competitive Diffusion Model | 2021 | VLDB | 5.2840289e-05 |
| 10,638 | Enabling Efficient Direct Update on Rule-Based Compressed Graph | 2026 | SIGMOD | 4.9793485e-05 |
| 11,663 | Host Profit Maximization: Leveraging Performance Incentives and User Flexibility | 2024 | VLDB | 4.9793485e-05 |
| 11,718 | Mitigating Filter Bubbles Under a Competitive Diffusion Model | 2023 | SIGMOD | 4.9793485e-05 |
Previous
Page 1 / 1
Next
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 |
|---|---|---|---|---|
| 320 | Influence Maximization in Near-Linear Time: A Martingale Approach | 2015 | SIGMOD | 0.00021143147 |
| 455 | Stop-and-Stare: Optimal Sampling Algorithms for Viral Marketing in Billion-scale Networks | 2016 | SIGMOD | 0.0001796092 |
| 1,474 | Online Processing Algorithms for Influence Maximization | 2018 | SIGMOD | 0.00010556999 |
| 2,306 | Online Topic-Aware Influence Maximization | 2015 | VLDB | 8.6680219e-05 |
| 2,587 | From Competition to Complementarity: Comparative Influence Diffusion and Maximization | 2016 | VLDB | 8.2550609e-05 |
| 3,554 | Revisiting the Stop-and-Stare Algorithms for Influence Maximization | 2017 | VLDB | 7.2088217e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,911 | Revenue Maximization in Incentivized Social Advertising | 2017 | VLDB |
| 2 | 11,663 | Host Profit Maximization: Leveraging Performance Incentives and User Flexibility | 2024 | VLDB |
| 3 | 299 | A Data-Based Approach to Social Influence Maximization | 2012 | VLDB |
| 4 | 2,697 | Efficient Algorithms for Budgeted Influence Maximization on Massive Social Networks | 2020 | VLDB |
| 5 | 320 | Influence Maximization in Near-Linear Time: A Martingale Approach | 2015 | SIGMOD |
| 6 | 5,823 | Continuous Influence Maximization: What Discounts Should We Offer to Social Network Users? | 2016 | SIGMOD |
| 7 | 4,652 | Efficient Algorithms for Adaptive Influence Maximization | 2018 | VLDB |
| 8 | 2,587 | From Competition to Complementarity: Comparative Influence Diffusion and Maximization | 2016 | VLDB |
| 9 | 7,310 | Collective Influence Maximization for Multiple Competing Products with an Awareness-to-Influence Model | 2021 | VLDB |
| 10 | 8,757 | Maximizing Social Welfare in a Competitive Diffusion Model | 2021 | VLDB |