Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model

The widespread of rumors is no doubt harmful to information security and social stability. Therefore, it is necessary to control it effectively. In this paper, a dynamic model with a double-layer interaction process is proposed to explore the impact of network interaction and dynamic evolution. Cons...
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Autor*in:	Haofei Yin [verfasserIn] Zhiping Wang [verfasserIn] Yue Gou [verfasserIn] Zhaohui Xu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Analytical models complex networks dynamics numerical simulation propagation

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 8(2020), Seite 115273-115286
Übergeordnetes Werk:	volume:8 ; year:2020 ; pages:115273-115286

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2020.3004455

Katalog-ID:	DOAJ058852905

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520			\|a The widespread of rumors is no doubt harmful to information security and social stability. Therefore, it is necessary to control it effectively. In this paper, a dynamic model with a double-layer interaction process is proposed to explore the impact of network interaction and dynamic evolution. Considering the individual heterogeneity and time-varying, the probability of node state transformation is not a fixed parameter, but closely related to the degree and hyperdegree of each node in the time step. Then, the theoretical analysis is conducted by Microscopic Markov Chain Approach and the impact of each parameter is tested. The simulation results show that the rumor diffusion is not only related to the interaction of the network, but also affected by the dynamic evolution of the network structure. Finally, according to the simulation results, the corresponding control strategies are proposed. The model is universal and can be reduced to traditional double-layer network model or single-layer dynamic hypernetwork model.
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spelling	10.1109/ACCESS.2020.3004455 doi (DE-627)DOAJ058852905 (DE-599)DOAJ3c9a444f01f041b79b43626d49403c27 DE-627 ger DE-627 rakwb eng TK1-9971 Haofei Yin verfasserin aut Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The widespread of rumors is no doubt harmful to information security and social stability. Therefore, it is necessary to control it effectively. In this paper, a dynamic model with a double-layer interaction process is proposed to explore the impact of network interaction and dynamic evolution. Considering the individual heterogeneity and time-varying, the probability of node state transformation is not a fixed parameter, but closely related to the degree and hyperdegree of each node in the time step. Then, the theoretical analysis is conducted by Microscopic Markov Chain Approach and the impact of each parameter is tested. The simulation results show that the rumor diffusion is not only related to the interaction of the network, but also affected by the dynamic evolution of the network structure. Finally, according to the simulation results, the corresponding control strategies are proposed. The model is universal and can be reduced to traditional double-layer network model or single-layer dynamic hypernetwork model. Analytical models complex networks dynamics numerical simulation propagation Electrical engineering. Electronics. Nuclear engineering Zhiping Wang verfasserin aut Yue Gou verfasserin aut Zhaohui Xu verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 115273-115286 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:115273-115286 https://doi.org/10.1109/ACCESS.2020.3004455 kostenfrei https://doaj.org/article/3c9a444f01f041b79b43626d49403c27 kostenfrei https://ieeexplore.ieee.org/document/9123335/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 115273-115286
allfields_unstemmed	10.1109/ACCESS.2020.3004455 doi (DE-627)DOAJ058852905 (DE-599)DOAJ3c9a444f01f041b79b43626d49403c27 DE-627 ger DE-627 rakwb eng TK1-9971 Haofei Yin verfasserin aut Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The widespread of rumors is no doubt harmful to information security and social stability. Therefore, it is necessary to control it effectively. In this paper, a dynamic model with a double-layer interaction process is proposed to explore the impact of network interaction and dynamic evolution. Considering the individual heterogeneity and time-varying, the probability of node state transformation is not a fixed parameter, but closely related to the degree and hyperdegree of each node in the time step. Then, the theoretical analysis is conducted by Microscopic Markov Chain Approach and the impact of each parameter is tested. The simulation results show that the rumor diffusion is not only related to the interaction of the network, but also affected by the dynamic evolution of the network structure. Finally, according to the simulation results, the corresponding control strategies are proposed. The model is universal and can be reduced to traditional double-layer network model or single-layer dynamic hypernetwork model. Analytical models complex networks dynamics numerical simulation propagation Electrical engineering. Electronics. Nuclear engineering Zhiping Wang verfasserin aut Yue Gou verfasserin aut Zhaohui Xu verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 115273-115286 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:115273-115286 https://doi.org/10.1109/ACCESS.2020.3004455 kostenfrei https://doaj.org/article/3c9a444f01f041b79b43626d49403c27 kostenfrei https://ieeexplore.ieee.org/document/9123335/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 115273-115286
allfieldsGer	10.1109/ACCESS.2020.3004455 doi (DE-627)DOAJ058852905 (DE-599)DOAJ3c9a444f01f041b79b43626d49403c27 DE-627 ger DE-627 rakwb eng TK1-9971 Haofei Yin verfasserin aut Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The widespread of rumors is no doubt harmful to information security and social stability. Therefore, it is necessary to control it effectively. In this paper, a dynamic model with a double-layer interaction process is proposed to explore the impact of network interaction and dynamic evolution. Considering the individual heterogeneity and time-varying, the probability of node state transformation is not a fixed parameter, but closely related to the degree and hyperdegree of each node in the time step. Then, the theoretical analysis is conducted by Microscopic Markov Chain Approach and the impact of each parameter is tested. The simulation results show that the rumor diffusion is not only related to the interaction of the network, but also affected by the dynamic evolution of the network structure. Finally, according to the simulation results, the corresponding control strategies are proposed. The model is universal and can be reduced to traditional double-layer network model or single-layer dynamic hypernetwork model. Analytical models complex networks dynamics numerical simulation propagation Electrical engineering. Electronics. Nuclear engineering Zhiping Wang verfasserin aut Yue Gou verfasserin aut Zhaohui Xu verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 115273-115286 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:115273-115286 https://doi.org/10.1109/ACCESS.2020.3004455 kostenfrei https://doaj.org/article/3c9a444f01f041b79b43626d49403c27 kostenfrei https://ieeexplore.ieee.org/document/9123335/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 115273-115286
allfieldsSound	10.1109/ACCESS.2020.3004455 doi (DE-627)DOAJ058852905 (DE-599)DOAJ3c9a444f01f041b79b43626d49403c27 DE-627 ger DE-627 rakwb eng TK1-9971 Haofei Yin verfasserin aut Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The widespread of rumors is no doubt harmful to information security and social stability. Therefore, it is necessary to control it effectively. In this paper, a dynamic model with a double-layer interaction process is proposed to explore the impact of network interaction and dynamic evolution. Considering the individual heterogeneity and time-varying, the probability of node state transformation is not a fixed parameter, but closely related to the degree and hyperdegree of each node in the time step. Then, the theoretical analysis is conducted by Microscopic Markov Chain Approach and the impact of each parameter is tested. The simulation results show that the rumor diffusion is not only related to the interaction of the network, but also affected by the dynamic evolution of the network structure. Finally, according to the simulation results, the corresponding control strategies are proposed. The model is universal and can be reduced to traditional double-layer network model or single-layer dynamic hypernetwork model. Analytical models complex networks dynamics numerical simulation propagation Electrical engineering. Electronics. Nuclear engineering Zhiping Wang verfasserin aut Yue Gou verfasserin aut Zhaohui Xu verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 115273-115286 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:115273-115286 https://doi.org/10.1109/ACCESS.2020.3004455 kostenfrei https://doaj.org/article/3c9a444f01f041b79b43626d49403c27 kostenfrei https://ieeexplore.ieee.org/document/9123335/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 115273-115286
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source	In IEEE Access 8(2020), Seite 115273-115286 volume:8 year:2020 pages:115273-115286
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callnumber-first	T - Technology
author	Haofei Yin
spellingShingle	Haofei Yin misc TK1-9971 misc Analytical models misc complex networks misc dynamics misc numerical simulation misc propagation misc Electrical engineering. Electronics. Nuclear engineering Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model
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topic_title	TK1-9971 Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model Analytical models complex networks dynamics numerical simulation propagation
topic	misc TK1-9971 misc Analytical models misc complex networks misc dynamics misc numerical simulation misc propagation misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Analytical models misc complex networks misc dynamics misc numerical simulation misc propagation misc Electrical engineering. Electronics. Nuclear engineering
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title	Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model
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title_full	Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model
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title_sort	rumor diffusion and control based on double-layer dynamic evolution model
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title_auth	Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model
abstract	The widespread of rumors is no doubt harmful to information security and social stability. Therefore, it is necessary to control it effectively. In this paper, a dynamic model with a double-layer interaction process is proposed to explore the impact of network interaction and dynamic evolution. Considering the individual heterogeneity and time-varying, the probability of node state transformation is not a fixed parameter, but closely related to the degree and hyperdegree of each node in the time step. Then, the theoretical analysis is conducted by Microscopic Markov Chain Approach and the impact of each parameter is tested. The simulation results show that the rumor diffusion is not only related to the interaction of the network, but also affected by the dynamic evolution of the network structure. Finally, according to the simulation results, the corresponding control strategies are proposed. The model is universal and can be reduced to traditional double-layer network model or single-layer dynamic hypernetwork model.
abstractGer	The widespread of rumors is no doubt harmful to information security and social stability. Therefore, it is necessary to control it effectively. In this paper, a dynamic model with a double-layer interaction process is proposed to explore the impact of network interaction and dynamic evolution. Considering the individual heterogeneity and time-varying, the probability of node state transformation is not a fixed parameter, but closely related to the degree and hyperdegree of each node in the time step. Then, the theoretical analysis is conducted by Microscopic Markov Chain Approach and the impact of each parameter is tested. The simulation results show that the rumor diffusion is not only related to the interaction of the network, but also affected by the dynamic evolution of the network structure. Finally, according to the simulation results, the corresponding control strategies are proposed. The model is universal and can be reduced to traditional double-layer network model or single-layer dynamic hypernetwork model.
abstract_unstemmed	The widespread of rumors is no doubt harmful to information security and social stability. Therefore, it is necessary to control it effectively. In this paper, a dynamic model with a double-layer interaction process is proposed to explore the impact of network interaction and dynamic evolution. Considering the individual heterogeneity and time-varying, the probability of node state transformation is not a fixed parameter, but closely related to the degree and hyperdegree of each node in the time step. Then, the theoretical analysis is conducted by Microscopic Markov Chain Approach and the impact of each parameter is tested. The simulation results show that the rumor diffusion is not only related to the interaction of the network, but also affected by the dynamic evolution of the network structure. Finally, according to the simulation results, the corresponding control strategies are proposed. The model is universal and can be reduced to traditional double-layer network model or single-layer dynamic hypernetwork model.
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title_short	Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model
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