Mean‑field dynamics of the non‑consensus opinion model
article
In 2009, Shao et al. (Phys Rev Lett 103(1):018701, 2009) introduced the Non-consensus
opinion (NCO) model, which allows different opinions to coexist in the steady state.
We propose a mean-field-based dynamical model for the NCO model on networks
with low degree correlation, which reveals the mechanism of opinion formation
in the NCO model. This mean-field model provides a new way of estimating important
system properties such as the fraction of a certain opinion F, the critical threshold fc ,
and the size of the largest connected cluster for a given opinion s1 . It offers an accurate
estimation in less time than the Monte Carlo simulations. The scale invariance
of the NCO model is discussed. The variation in the degree of nodes holding different
opinions in the dynamics of the NCO model is investigated. The trends in the dynamics
of the NCO model are also revealed. This approach can be applied to real-world social
networks, providing a method of analyzing opinion dynamics in human society.
opinion (NCO) model, which allows different opinions to coexist in the steady state.
We propose a mean-field-based dynamical model for the NCO model on networks
with low degree correlation, which reveals the mechanism of opinion formation
in the NCO model. This mean-field model provides a new way of estimating important
system properties such as the fraction of a certain opinion F, the critical threshold fc ,
and the size of the largest connected cluster for a given opinion s1 . It offers an accurate
estimation in less time than the Monte Carlo simulations. The scale invariance
of the NCO model is discussed. The variation in the degree of nodes holding different
opinions in the dynamics of the NCO model is investigated. The trends in the dynamics
of the NCO model are also revealed. This approach can be applied to real-world social
networks, providing a method of analyzing opinion dynamics in human society.
TNO Identifier
1003365
Source
Applied Network Science, 9(47)