A Data-Based Approach to Social Influence Maximization
Summary: Introduces credit distribution, a data-driven model using historical propagation traces to learn influence flow and estimate spread. Shows NP-hardness and submodularity of the induced spread; offers a scalable approximation outperforming graph-only baselines. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Amit Goyal (University of British Columbia)
- 2. Francesco Bonchi (Yahoo)
- 3. Laks V. S. Lakshmanan (University of British Columbia)
BibTeX Citation
@article{goyal_vldb12,
title = {{A Data-Based Approach to Social Influence Maximization}},
author = {Goyal, Amit and Bonchi, Francesco and Lakshmanan, Laks V. S.},
journal = {PVLDB},
series = {{VLDB} '12},
volume = {5},
number = {1},
pages = {73--84},
doi = {10.14778/3402755.3402767},
url = {https://doi.org/10.14778/3402755.3402767},
year = {2012}
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