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Influence analysis of information erupted on social networks based onSIRmodel

Author

Listed:
  • Xue Zhou

    (College of Electronics and Information Engineering, Sichuan University, Chengdu 610064, P. R. China)

  • Yong Hu

    (College of Electronics and Information Engineering, Sichuan University, Chengdu 610064, P. R. China)

  • Yue Wu

    (School of Mathematics and Computer Science, Xihua University, Chengdu, Sichuan 610039, P. R. China)

  • Xi Xiong

    (College of Network Engineering, Chengdu University of Information Technology, Chengdu, Sichuan 610225, P. R. China)

Abstract

In this paper, according to the similarity of chain reaction principle and the characteristics of information propagation on social network, we proposed a new word "information bomb". Based on the complex networks andSIRmodel, dynamical evolution equations were setup. Then methods used to evaluate the four indexes of bomb power were given, including influence breadth, influence strength, peak time and relaxation time. At last, the power of information was ascertained through these indexes. The process of information propagation is simulated to illustrate the spreading characteristics through the results. Then parameters which impact on the power of information bomb are analyzed and some methods which control the propagation of information are given.

Suggested Citation

  • Xue Zhou & Yong Hu & Yue Wu & Xi Xiong, 2015. "Influence analysis of information erupted on social networks based onSIRmodel," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 26(02), pages 1-11.
    • Handle: RePEc:wsi:ijmpcx:v:26:y:2015:i:02:n:s0129183115500187
    DOI: 10.1142/S0129183115500187
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    Citations

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    Cited by:

    1. Wang, Haiying & Wang, Jun & Small, Michael, 2018. "Knowledge transmission model with differing initial transmission and retransmission process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 478-488.
    2. Liu, Yu & Wang, Bai & Wu, Bin & Shang, Suiming & Zhang, Yunlei & Shi, Chuan, 2016. "Characterizing super-spreading in microblog: An epidemic-based information propagation model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 202-218.
    3. Chen, Zhihua & An, Haizhong & An, Feng & Guan, Qing & Hao, Xiaoqing, 2018. "Structural risk evaluation of global gas trade by a network-based dynamics simulation model," Energy, Elsevier, vol. 159(C), pages 457-471.
    4. Zhao, Danling & Sun, Jianbin & Tan, Yuejin & Wu, Jianhong & Dou, Yajie, 2018. "An extended SEIR model considering homepage effect for the information propagation of online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1019-1031.
    5. Yao, Yao & Li, Yuanyuan & Xiong, Xi & Wu, Yue & Lin, Honggang & Ju, Shenggen, 2020. "An interactive propagation model of multiple information in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    6. Wang, Dan & Cheng, Shun-Jun, 2016. "A two-stage broadcast message propagation model in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1286-1293.
    7. Ping Jiang & Xiangbin Yan, 2019. "A quantitative model for the spread of online information," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 1981-2001, July.

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