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Multi-hop analysis method for rich-club phenomenon of influence maximization in social networks

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Abstract

When studying the Influence Maximization (IM) problem in social networks, it is found that the initial seed nodes selected by some heuristic algorithms have the characteristics of aggregation. This situation is called the rich club phenomenon of seed sets. Once the seed node is over-aggregated, it will limit the spread of influence. Therefore, analyzing the rich-club phenomenon is necessary for solving the IM problem. The paper proposes the rich club coefficient and reactivation rate to quantitatively analyze this phenomenon. The analysis mainly focuses on the relationship between the hop distance and the propagation probability. In addition, the relationship between the rich club phenomenon and the IM problem is also an aspect of concern. When dealing with the main aspects, a key problem needs to be solved, which is that the optimal range of hop is different under different propagation probabilities. To solve this problem, the Multi Hop Remove (MHR) algorithm is proposed, which is based on the independent cascade model. By the MHR algorithm, the hop range is determined under different propagation probabilities. According to our experimental results, the more serious the rich club phenomenon accumulates, the smaller the influence spread. To reduce the obstruction of this phenomenon, the multi-hop selection of seed nodes is a superior solution.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China [Grant No. 71772107] and Shandong Nature Science Foundation of China [Grant No. ZR2020MF044]. Moreover, the author thanks every reviewer who provided valuable comments and feedback. Similarly, we thank the researchers Xiangbo Tian, Jianyi Zhang, Yuying Liu who guided the writing of the paper. Finally, the author would like to thank Qiang Shi, the researcher who collected the data for the experiment.

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Authors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

    Xiuliang Duan, Liqing Qiu & Chengai Sun

  2. College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, 266590, Qingdao, China

    Qiang Shi

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  1. Xiuliang Duan
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  2. Liqing Qiu
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Correspondence to Liqing Qiu.

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Duan, X., Qiu, L., Sun, C. et al. Multi-hop analysis method for rich-club phenomenon of influence maximization in social networks. Appl Intell 52, 8721–8734 (2022). https://doi.org/10.1007/s10489-021-02818-0

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