Conference Proceedings
Finding temporal influential users over evolving social networks
S Huang, Z Bao, JS Culpepper, B Zhang
Proceedings International Conference on Data Engineering | IEEE | Published : 2019
Abstract
Influence maximization (IM) continues to be a key research problem in social networks. The goal is to find a small seed set of target users that have the greatest influence in the network under various stochastic diffusion models. While significant progress has been made on the IM problem in recent years, several interesting challenges remain. For example, social networks in reality are constantly evolving, and 'important' users with the most influence also change over time. As a result, several recent studies have proposed approaches to update the seed set as the social networks evolve. However, this seed set is not guaranteed to be the best seed set over a period of time. In this paper we ..
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Awarded by Australian Research Council
Funding Acknowledgements
This work was partially supported by ARC DP170102726, DP180102050, DP170102231, and NSFC 61728204, 91646204. Zhifeng Bao is a recipient of Google Faculty Award.