Influence Maximization with Novelty Decay in Social Networks

Feng, Shanshan, Cheng, Xuefeng, Cong, Gao, Zeng, Yifeng, Chee, Yeow Meng and Xiang, Yanping (2014) Influence Maximization with Novelty Decay in Social Networks. In: Proceedings of the twenty-eighth AAAI Conference on Artificial Intelligence and the twenty-sixth Innovative Applications of Artificial Intelligence Conference. Proceedings of the AAAI Conference on Artificial Intelligence . AAAI Press, Palo Alto, pp. 37-43. ISBN 9781577356615, 9781577356776, 9781577356783, 9781577356790, 9781577356806

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Influence maximization problem is to find a set of seed nodes in a social network such that their influence spread is maximized under certain propagation models. A few algorithms have been proposed for solving this problem. However, they have not considered the impact of novelty decay on influence propagation, i.e., repeated exposures will have diminishing influence on users. In this paper, we consider the problem of influence maximization with novelty decay (IMND). We investigate the effect of novelty decay on influence propagation on real-life datasets and formulate the IMND problem. We further analyze the problem properties and propose an influence estimation technique. We demonstrate the performance of our algorithms on four social networks.

Item Type: Book Section
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: John Coen
Date Deposited: 09 Jul 2020 08:31
Last Modified: 31 Jul 2021 11:46

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