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SE2IR Invest Market Rumor Spreading Model Considering Hesitating Mechanism

  • Hongxing Yao EMAIL logo and Xiangyang Gao
Published/Copyright: March 18, 2019
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Abstract

According to the actual situation of investor network, a SE2IR rumor spreading model with hesitating mechanism is proposed, and the corresponding mean-field equations is obtained on scale-free network. In this paper, we first combine the theory of spreading dynamics and find out the basic reproductive number R0. And then analyzes the stability of the rumor-free equilibrium and the final rumor size. Finally, we discuss random immune strategies and target immune strategies for the rumor spreading, respectively. Through numerical simulation, we can draw the following conclusions: Reducing the fuzziness and attractiveness of invest market rumor can effectively reduce the impact of rumor. And the target immunization strategy is more effective than the random immunization strategy for the communicators in the invest investor network.


Supported by the National Natural Science Foundation of China (71271103)


References

[1] Daley D J, Kendall D G. Epidemics and rumours. Nature, 1964, 204(4963): 1118–1118.10.1038/2041118a0Search in Google Scholar PubMed

[2] Maki D, Thomson M. Mathematical models and applications. Prentice-Hall, Englewood Cliffs, 1973.Search in Google Scholar

[3] Zanette D H. Dynamics of rumor propagation on small-world networks. Physical Review E: Statistical Nonlinear & Soft Matter Physics, 2002, 65(1): 041908.10.1103/PhysRevE.65.041908Search in Google Scholar PubMed

[4] Moreno Y, Nekovee M, Pacheco A F. Dynamics of rumor spreading in complex networks. Physical Review E: Statistical Nonlinear & Soft Matter Physics, 2003, 69(2): 066130.10.1103/PhysRevE.69.066130Search in Google Scholar PubMed

[5] Nekovee M, Moreno Y, Bianconi G, et al. Theory of rumor spreading in complex social networks. Physica A: Statistical Mechanics & Its Applications, 2008, 374(1): 457–470.10.1016/j.physa.2006.07.017Search in Google Scholar

[6] Pan Z F, Wang X F, Li X. Research on rumor propagation simulation on scale-free networks with variable clustering coefficients. Journal of System Simulation, 2006, 18(8): 2346–2348.Search in Google Scholar

[7] Zhao L J, Wang Q, Cheng J J, et al. Rumor spreading model with consideration of forgetting mechanism: A case of online blogging LiveJournal. Physica A: Statistical Mechanics & Its Applications, 2011, 390(13): 2619–2625.10.1016/j.physa.2011.03.010Search in Google Scholar

[8] Zhao L J, Wang J J, Chen Y C, et al. SIHR rumor spreading model in social networks. Physica A, 2012, 391(7): 2444–2453.10.1016/j.physa.2011.12.008Search in Google Scholar

[9] Wang Y Q, Yang X Y, Han Y L, et al. Rumor spreading model with trust mechanism in complex social networks. Communications in Theoretical Physics, 2013, 59(4): 510–516.10.1088/0253-6102/59/4/21Search in Google Scholar

[10] Zhao L J, Xie W L, Gao H O, et al. A rumor spreading model with variable forgetting rate. Physica A: Statistical Mechanics & Its Applications, 2013, 392(23): 6146–6154.10.1016/j.physa.2013.07.080Search in Google Scholar

[11] Zhao L J, Qiu X Y, Wang X L, et al. Rumor spreading model considering forgetting and remembering mechanisms in inhomogeneous networks. Physica A: Statistical Mechanics & Its Applications, 2013, 392(4): 987–994.10.1016/j.physa.2012.10.031Search in Google Scholar

[12] Wang J J, Zhao L J, Huang R B. SIRaRu rumor spreading model in complex networks. Physica A: Statistical Mechanics & Its Applications, 2014, 398(15): 43–55.10.1016/j.physa.2013.12.004Search in Google Scholar

[13] Afassinou K. Analysis of the impact of education rate on the rumor spreading mechanism. Physica A: Statistical Mechanics & Its Applications, 2014, 414(10): 43–52.10.1016/j.physa.2014.07.041Search in Google Scholar

[14] Huo L A, Wang L, Song N X, et al. Rumor spreading model considering the activity of spreaders in the homogeneous network. Physica A: Statistical Mechanics & Its Applications, 2017, 468: 855–865.10.1016/j.physa.2016.11.039Search in Google Scholar

[15] Hale J K. Ordinary differential equations, pure and applied mathematics. Wiley-Interscience, New York, NY, USA, 1969.Search in Google Scholar

[16] Liu Q, Li T, Sun M. The analysis of an SEIR rumor propagation model on heterogeneous network. Physica A: Statistical Mechanics & Its Applications, 2017, 469: 372–380.10.1016/j.physa.2016.11.067Search in Google Scholar

[17] Xia L L, Jiang G P, Song B, et al. Rumor spreading model considering hesitating mechanism in complex social networks. Physica A: Statistical Mechanics & Its Applications, 2015, 437: 295–303.10.1016/j.physa.2015.05.113Search in Google Scholar

[18] Van den Driessche P, Watmough J. Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Mathematical Biosciences, 2002, 180(1–2): 29–48.10.1016/S0025-5564(02)00108-6Search in Google Scholar PubMed

[19] Li K, Small M, Zhang H, et al. Epidemic outbreaks on networks with effective contacts. Nonlinear Analysis: Real World Applications, 2010, 11(2): 1017–1025.10.1016/j.nonrwa.2009.01.046Search in Google Scholar

[20] Zhang J, Jin Z. The analysis of an epidemic model on networks. Applied Mathematics & Computation, 2011, 217(17): 7053–7064.10.1016/j.amc.2010.09.063Search in Google Scholar

[21] Fu X, Small M, Walker D M, et al. Epidemic dynamics on scale-free networks with piecewise linear infectivity and immunization. Physical Review E: Statistical Nonlinear & Soft Matter Physics, 2008, 77(2): 036113.10.1103/PhysRevE.77.036113Search in Google Scholar PubMed

Received: 2018-01-18
Accepted: 2018-05-23
Published Online: 2019-03-18

© 2019 Walter de Gruyter GmbH, Berlin/Boston

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