@article{M2737B774,
title = "Fast Influence Maximization in Social Networks",
journal = "Journal of KIISE, JOK",
year = "2017",
issn = "2383-630X",
doi = "10.5626/JOK.2017.44.10.1105",
author = "Yun-Yong Ko,Kyung-Jae Cho,Sang-Wook Kim",
keywords = "social network,information diffusion,influence maximization,community detection",
abstract = "Influence maximization (IM) is the problem of finding a seed set composed of k nodes that maximizes the influence spread in social networks. However, one of the biggest problems of existing solutions for IM is that it takes too much time to select a k-seed set. This performance issue occurs at the micro and macro levels. In this paper, we propose a fast hybrid method that addresses two issues at micro and macro levels. Furthermore, we propose a path-based community detection method that helps to select a good seed set. The results of our experiment with four real-world datasets show that the proposed method resolves the two issues at the micro and macro levels and selects a good k-seed set."
}