dc.contributorUniversidade de São Paulo (USP)
dc.contributorUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2022-04-29T07:25:53Z
dc.date.accessioned2022-12-20T02:32:41Z
dc.date.available2022-04-29T07:25:53Z
dc.date.available2022-12-20T02:32:41Z
dc.date.created2022-04-29T07:25:53Z
dc.date.issued2015-02-23
dc.identifierPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics, v. 91, n. 2, 2015.
dc.identifier1550-2376
dc.identifier1539-3755
dc.identifierhttp://hdl.handle.net/11449/227938
dc.identifier10.1103/PhysRevE.91.022813
dc.identifier2-s2.0-84923799433
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5408073
dc.description.abstractThis paper studies the Sznajd model for opinion formation in a population connected through a general network. A master equation describing the time evolution of opinions is presented and solved in a mean-field approximation. Although quite simple, this approximation allows us to capture the most important features regarding the steady states of the model. When spontaneous opinion changes are included, a discontinuous transition from consensus to polarization can be found as the rate of spontaneous change is increased. In this case we show that a hybrid mean-field approach including interactions between second nearest neighbors is necessary to estimate correctly the critical point of the transition. The analytical prediction of the critical point is also compared with numerical simulations in a wide variety of networks, in particular Barabási-Albert networks, finding reasonable agreement despite the strong approximations involved. The same hybrid approach that made it possible to deal with second-order neighbors could just as well be adapted to treat other problems such as epidemic spreading or predator-prey systems.
dc.languageeng
dc.relationPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
dc.sourceScopus
dc.titleMean-field approximation for the Sznajd model in complex networks
dc.typeArtículos de revistas


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