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Community analysis of influential nodes for information diffusion on a social network

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4 Author(s)
Masahiro Kimura ; Department of Electronics and Informatics, Faculty of Science and Technology, Ryukoku University, Otsu 520-2194, Japan ; Kazumasa Yamakawa ; Kazumi Saito ; Hiroshi Motoda

We consider the problem of finding influential nodes for information diffusion on a social network under the independent cascade model. It is known that the greedy algorithm can give a good approximate solution for the problem. Aiming to obtain efficient methods for finding better approximate solutions, we explore what structural feature of the underlying network is relevant to the greedy solution that is the approximate solution by the greedy algorithm. We focus on the SR-community structure, and analyze the greedy solution in terms of the SR-community structure. Using real large social networks, we experimentally demonstrate that the SR-community structure can be more strongly correlated with the greedy solution than the community structure introduced by Newman and Leicht.

Published in:

2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)

Date of Conference:

1-8 June 2008