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Influence maximization based on SATS scheme in social networks

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Abstract

Key user identification for messages propagation constitutes one of the most important topics in social networks. The success of the information spreading depends on the selection of the key users. Besides the social attributes of users, the topology structure of the networks should be considered in this mechanism to ensure performance. In this paper, we propose the Social Attributes and Topology Structure (SATS) scheme for discovering key users in social networks. Firstly, the proposed SATS scheme utilizes four types of social attributes, and we extract the key social attributes. Then, we explore the feature of topology structure, in which social influence is defined and top-k influential users can be identified. Finally, the experiment results show that the proposed SATS scheme has effective propagation ability in the Susceptible Infected Recovered model, we can find the nodes which have more effects on network robustness while encountering the intentional attack by SATS scheme, and the proposed SATS scheme achieves better performance in identifying key users compared with some baseline approaches.

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Acknowledgements

The authors would like to thank the National Natural Science Foundation of China (NOs. U1905211, 61771140, 62171132).

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Authors and Affiliations

  1. College of Computer and Cyber Security, Fujian Normal University, Fuzhou, Fujian, China

    Xinxin Zhang, Li Xu & Zhaobin Zhou

  2. Fujian Provincial Key Laboratory of Network Security and Cryptology, Fujian Normal University, Fuzhou, Fujian, China

    Xinxin Zhang, Li Xu & Zhaobin Zhou

  3. The School of Computer Science, Fudan University, Shanghai, China

    Min Gao

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  1. Xinxin Zhang
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  2. Min Gao
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  3. Li Xu
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  4. Zhaobin Zhou
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Correspondence to Zhaobin Zhou.

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Zhang, X., Gao, M., Xu, L. et al. Influence maximization based on SATS scheme in social networks. Computing 105, 275–292 (2023). https://doi.org/10.1007/s00607-022-01125-x

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