(2023) Alencar, David Santana Marques; Alves, Tayroni Francisco de Alencar; Alves, Gladstone de Alencar; Macedo Filho, Antonio de; Ferreira, Ronan Silva; Lima, Francisco Welington de Sousa; Plascak, João Antônio
A discrete version of opinion dynamics systems, based on the Biswas–Chatterjee–Sen
(BChS) model, has been studied on Barabási–Albert networks (BANs). In this model, depending
on a pre-defined noise parameter, the mutual affinities can assign either positive or negative values.
By employing extensive computer simulations with Monte Carlo algorithms, allied with finite-size
scaling hypothesis, second-order phase transitions have been observed. The corresponding critical
noise and the usual ratios of the critical exponents have been computed, in the thermodynamic limit,
as a function of the average connectivity. The effective dimension of the system, defined through a
hyper-scaling relation, is close to one, and it turns out to be connectivity-independent. The results
also indicate that the discrete BChS model has a similar behavior on directed Barabási–Albert networks
(DBANs), as well as on Erdös–Rènyi random graphs (ERRGs) and directed ERRGs random graphs
(DERRGs). However, unlike the model on ERRGs and DERRGs, which has the same critical behavior
for the average connectivity going to infinity, the model on BANs is in a different universality class to
its DBANs counterpart in the whole range of the studied connectivities.
