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An information propagation model for social networks based on continuous-time quantum walk

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Abstract

Existing social network simulation models exhibit several limitations, including extensive iteration requirements and multiple control parameters. In this study, an information propagation model based on continuous-time quantum walk (CTQW-IPM) is introduced to rank crucial individuals in undirected social networks. In the proposed CTQW-IPM, arbitrary individuals (or groups) can be specified as initial diffusion dynamic elements through preset probability amplitudes. Information diffusion on a global reachable path is then simulated by an evolution operator, as individual degrees of cruciality are estimated from probability distributions acquired from quantum observations. CTQW-IPM does not require iterations, due to the non-randomness of CTQW, and does not include extensive computations as complex cascade diffusion processes are replaced by evolution operators. Experimental comparisons of CTQW-IPM and several conventional models showed their ranking of crucial individuals exhibited a strong correlation, with nearly every individual in the social network assigned a unique measured value based on the rate of distinguishability. CTQW-IPM also outperformed other algorithms in influence maximization problems, as measured by the resulting spread size.

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Funding

This work is supported by the Jilin Provincial Department of Science and Technology, China (No. 20210201075GX).

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Authors and Affiliations

  1. School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China

    Fei Yan & Wen Liang

  2. Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, Japan

    Kaoru Hirota

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  1. Fei Yan
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  2. Wen Liang
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  3. Kaoru Hirota
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Correspondence to Fei Yan.

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Yan, F., Liang, W. & Hirota, K. An information propagation model for social networks based on continuous-time quantum walk. Neural Comput & Applic 34, 13455–13468 (2022). https://doi.org/10.1007/s00521-022-07168-7

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  • DOI: https://doi.org/10.1007/s00521-022-07168-7

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