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2010

Extracting influential nodes on a social network for information diffusion

8 years 10 months ago
Extracting influential nodes on a social network for information diffusion
We address the combinatorial optimization problem of finding the most influential nodes on a large-scale social network for two widely-used fundamental stochastic diffusion models. The past study showed that a greedy strategy can give a good approximate solution to the problem. However, a conventional greedy method faces a computational problem. We propose a method of efficiently finding a good approximate solution to the problem under the greedy algorithm on the basis of bond percolation and graph theory, and compare the proposed method with the conventional method in terms of computational complexity in order to theoretically evaluate its effectiveness. The results show that the proposed method is expected to achieve a great reduction in computational cost. We further experimentally demonstrate that the proposed method is much more efficient than the conventional method using large-scale real-world networks including blog networks. Keywords Social network analysis, Information diffu...
Masahiro Kimura, Kazumi Saito, Ryohei Nakano, Hiro
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2010
Where DATAMINE
Authors Masahiro Kimura, Kazumi Saito, Ryohei Nakano, Hiroshi Motoda
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