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SIR-IM: SIR rumor spreading model with influence mechanism in social networks

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Abstract

Rumor, with the fast speed of transmission, may bring us panic, even economic loss. Thus, it is significant for us to take effective steps to control the rumor spreading. Unfortunately, most of the existing works ignore that the spreading probability is not a constant, but depends on the number of spreaders currently. That is to say, the more spreaders, the larger spreading probability. In order to overcome this shortcoming, in this paper, we propose a novel susceptible–infected–removed (SIR) rumor spreading model with the influence mechanism, called SIR-IM, which first incorporates the number of current spreaders into the spreading probability. Then, it employs time function to describe the rate of people from spreader to stifler as time goes on. Moreover, we not only derive mean-field equations to describe the dynamics of our SIR model, but also give theoretical analysis. Numerical simulations are conducted on social networks, which show that the influence mechanism can accelerate the rumor spreading.

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Acknowledgements

This study was funded by by the Nature Science Foundation of China (Grant Numbers 61502281, 71772107).

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Authors and Affiliations

  1. Shandong Province Key Laboratory of Wisdom Mine Information Technology, College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266510, China

    Liqing Qiu, Wei Jia, Weinan Niu, Mingjv Zhang & Shuqi Liu

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  1. Liqing Qiu
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  2. Wei Jia
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  3. Weinan Niu
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  4. Mingjv Zhang
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  5. Shuqi Liu
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Correspondence to Liqing Qiu.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by C. Jiang.

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Qiu, L., Jia, W., Niu, W. et al. SIR-IM: SIR rumor spreading model with influence mechanism in social networks. Soft Comput 25, 13949–13958 (2021). https://doi.org/10.1007/s00500-020-04915-7

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  • DOI: https://doi.org/10.1007/s00500-020-04915-7

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