Mitigating Filter Bubbles Under a Competitive Diffusion Model
Summary: Proposes a competitive diffusion model for mitigating filter bubbles, modeling competition among opposing viewpoints and exposure rewards. Offers a heuristic and two instance-dependent approximations; experiments on 4 datasets show strong mitigation. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Prithu Banerjee
- 2. Wei Chen
- 3. Laks V.S. Lakshmanan
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 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 |
| 1,801 | Online Processing Algorithms for Influence Maximization | 2018 | SIGMOD | 0.00010510943 |
| 2,371 | From Competition to Complementarity: Comparative Influence Diffusion and Maximization | 2016 | VLDB | 8.9482922e-05 |
| 4,220 | Revisiting the Stop-and-Stare Algorithms for Influence Maximization | 2017 | VLDB | 6.3493792e-05 |
| 5,938 | Maximizing Welfare in Social Networks under A Utility Driven Influence Diffusion model | 2019 | SIGMOD | 5.2650733e-05 |
| 6,450 | On A Quest for Combating Filter Bubbles and Misinformation | 2022 | SIGMOD | 5.0583557e-05 |
| 8,591 | Maximizing Social Welfare in a Competitive Diffusion Model | 2021 | VLDB | 4.4896282e-05 |
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