Directed propaganda in the majority-rule model
arXiv:2309.13026 · doi:10.1142/S0129183124500827
Abstract
Advertisement and propaganda have changed continuously in the past decades, mainly due to the people's interactions at online platforms and social networks, and operate nowadays reaching a highly specific online audience instead targeting the masses. The impacts of this new media effect, oriented directly for a specific audience, is investigated on this study, in which we focus on the opinion evolution of agents in the majority-rule model, considering the presence of directed propaganda. We introduce as the probability of a "positive" external propaganda and as the probability to the agents follow the external propaganda. Our results show that the usual majority-rule model stationary state is reached, with a full consensus, only for two cases, namely when the external propaganda is absent or when the media favors only one of the two opinions. However, even for a small influence of external propaganda, the final state is reached with a majority opinion dominating the population. For the case in which the propaganda influence is strong enough among the agents, we show that the consensus can not be reached at all, and we observe the polarization of opinions. In addition, we show through analytical and numerical results that the system undergoes an order-disorder phase transition that occurs at for the case .
Accepted for publication in International Journal of Modern Physics C
References in corpus (8)
- Modularity and community structure in networks
- Finding community structure in networks using the eigenvectors of matrices
- Statistical physics of social dynamics
- Sociophysics: A review of Galam models
- Role of conviction in nonequilibrium models of opinion formation
- Consequence of reputation in the Sznajd consensus model
- The first shall be last: selection-driven minority becomes majority
- The external field effect on the opinion formation based on the majority rule and the -voter models on the complete graph