Rumor Spreading of an SIHR Model in Heterogeneous Networks Based on Probability Generating Function
This paper focuses on the modeling of a rumor spreading in heterogeneous networks. Using the probability generating function method and pair approximation method, the current research obtains nonlinear differential equations to describe the dynamics of rumor spreading. The comparison between numeric...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2019/4268393 |
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| _version_ | 1850169320093515776 |
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| author | Jinxian Li Yanping Hu Zhen Jin |
| author_facet | Jinxian Li Yanping Hu Zhen Jin |
| author_sort | Jinxian Li |
| collection | DOAJ |
| description | This paper focuses on the modeling of a rumor spreading in heterogeneous networks. Using the probability generating function method and pair approximation method, the current research obtains nonlinear differential equations to describe the dynamics of rumor spreading. The comparison between numerical simulations and Monte Carlo simulations confirms the accuracy of our model. Furthermore, the threshold condition is also obtained in this paper. The numerical simulation results show that the heterogeneity of the network accelerates the outbreak of rumors but reduces the maximum density of spreader and the scale of rumors. The present study also examines the effects of parameters on rumor transmission and the differences between rumor transmission recovery mechanisms and disease transmission recovery mechanisms. |
| format | Article |
| id | doaj-art-a8a602e1118a4c04a86b386fc5633127 |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-a8a602e1118a4c04a86b386fc56331272025-08-20T02:20:45ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/42683934268393Rumor Spreading of an SIHR Model in Heterogeneous Networks Based on Probability Generating FunctionJinxian Li0Yanping Hu1Zhen Jin2School of Mathematical Sciences, Shanxi University, Taiyuan 030006, ChinaSchool of Mathematical Sciences, Shanxi University, Taiyuan 030006, ChinaShanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention, Taiyuan 030006, ChinaThis paper focuses on the modeling of a rumor spreading in heterogeneous networks. Using the probability generating function method and pair approximation method, the current research obtains nonlinear differential equations to describe the dynamics of rumor spreading. The comparison between numerical simulations and Monte Carlo simulations confirms the accuracy of our model. Furthermore, the threshold condition is also obtained in this paper. The numerical simulation results show that the heterogeneity of the network accelerates the outbreak of rumors but reduces the maximum density of spreader and the scale of rumors. The present study also examines the effects of parameters on rumor transmission and the differences between rumor transmission recovery mechanisms and disease transmission recovery mechanisms.http://dx.doi.org/10.1155/2019/4268393 |
| spellingShingle | Jinxian Li Yanping Hu Zhen Jin Rumor Spreading of an SIHR Model in Heterogeneous Networks Based on Probability Generating Function Complexity |
| title | Rumor Spreading of an SIHR Model in Heterogeneous Networks Based on Probability Generating Function |
| title_full | Rumor Spreading of an SIHR Model in Heterogeneous Networks Based on Probability Generating Function |
| title_fullStr | Rumor Spreading of an SIHR Model in Heterogeneous Networks Based on Probability Generating Function |
| title_full_unstemmed | Rumor Spreading of an SIHR Model in Heterogeneous Networks Based on Probability Generating Function |
| title_short | Rumor Spreading of an SIHR Model in Heterogeneous Networks Based on Probability Generating Function |
| title_sort | rumor spreading of an sihr model in heterogeneous networks based on probability generating function |
| url | http://dx.doi.org/10.1155/2019/4268393 |
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