Dynamic Influence Analysis in Evolving Networks
Summary: First real-time fully-dynamic index for influence analysis on evolving networks; redesign of the Borgs et al. sketch with efficient update algorithms. Adds reachability-tree and skipping, space-efficient RNGs; demonstrates millisecond influence estimates and ~10× faster influence maximization with provable non-degeneracy after arbitrary updates. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Naoto Ohsaka (Japan Science and Technology Agency; University of Tokyo)
- 2. Takuya Akiba (Japan Science and Technology Agency; National Institute of Informatics)
- 3. Yuichi Yoshida (Japan Science and Technology Agency; National Institute of Informatics; Preferred Infrastructure, Inc)
- 4. Ken-ichi Kawarabayashi (Japan Science and Technology Agency; National Institute of Informatics)
BibTeX Citation
@article{ohsaka_vldb16,
title = {{Dynamic Influence Analysis in Evolving Networks}},
author = {Ohsaka, Naoto and Akiba, Takuya and Yoshida, Yuichi and Kawarabayashi, Ken-ichi},
journal = {PVLDB},
series = {{VLDB} '16},
volume = {9},
number = {12},
pages = {1077--1088},
doi = {10.14778/2994509.2994525},
url = {https://doi.org/10.14778/2994509.2994525},
year = {2016}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,989 | Real-Time Influence Maximization on Dynamic Social Streams | 2017 | VLDB | 6.9716774e-05 |
| 5,786 | The Solution Distribution of Influence Maximization: A High-level Experimental Study on Three Algorithmic Approaches | 2020 | SIGMOD | 6.0890538e-05 |
| 7,963 | Coarsening Massive Influence Networks for Scalable Diffusion Analysis | 2017 | SIGMOD | 5.5177915e-05 |
| 11,216 | Influence Maximization via Vertex Countering | 2024 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 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 |
| 315 | Influence Maximization in Near-Linear Time: A Martingale Approach | 2015 | SIGMOD | 0.00021436156 |
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