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Double transition of information spreading in a two-layered network.
Wu, Jiao; Zheng, Muhua; Wang, Wei; Yang, Huijie; Gu, Changgui.
Afiliación
  • Wu J; Business School, University of Shanghai for Science and Technology, Shanghai 200093, China.
  • Zheng M; Departament de Física de la Matèria Condensada, Universitat de Barcelona, Barcelona 08028, Spain.
  • Wang W; Cybersecurity Research Institute, Sichuan University, Chengdu 610065, China.
  • Yang H; Business School, University of Shanghai for Science and Technology, Shanghai 200093, China.
  • Gu C; Business School, University of Shanghai for Science and Technology, Shanghai 200093, China.
Chaos ; 28(8): 083117, 2018 Aug.
Article en En | MEDLINE | ID: mdl-30180601
ABSTRACT
A great deal of significant progress has been seen in the study of information spreading on populations of networked individuals. A common point in many of the past studies is that there is only one transition in the phase diagram of the final accepted size versus the transmission probability. However, whether other factors alter this phenomenology is still under debate, especially for the case of information spreading through many channels and platforms. In the present study, we adopt a two-layered network to represent the interactions of multiple channels and propose a Susceptible-Accepted-Recovered information spreading model. Interestingly, our model shows a novel double transition including a continuous transition and a following discontinuous transition in the phase diagram, which originates from two outbreaks between the two layers of the network. Furthermore, we reveal that the key factors are a weak coupling condition between the two layers, a large adoption threshold, and the difference of the degree distributions between the two layers. Moreover, we also test the model in the coupled empirical social networks and find similar results as in the synthetic networks. Then, an edge-based compartmental theory is developed which fully explains all numerical results. Our findings may be of significance for understanding the secondary outbreaks of information in real life.

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: Chaos Asunto de la revista: CIENCIA Año: 2018 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: Chaos Asunto de la revista: CIENCIA Año: 2018 Tipo del documento: Article País de afiliación: China