Bounded confidence model on a still growing scale-free network
A. O. Sousa
Abstract
A Bounded Confidence (BC) model of socio-physics, in which the agents have continuous opinions and can influence each other only if the distance between their opinions is below a threshold, is simulated on a still growing scale-free network considering several different strategies: for each new node (or vertex), that is added to the network all individuals of the network have their opinions updated following a BC model recipe. The results obtained are compared with the original model, with numerical simulations on different graph structures and also when it is considered on the usual fixed BA network. In particular, the comparison with the latter leads us to conclude that it does not matter much whether the network is still growing or is fixed during the opinion dynamics.
Create a lesson
Related papers
Real-Space renormalization for the drawups and drawdowns of stochastic trajectories: universality classes for diffusion processes and random walks via the scale function
Cecile Monthus
Stochastic synthesis and degradation of arbitrary diffusive processes
Denis Boyer, Gabriel Mercado-Vásquez
Critical amplitudes of the Baxter-Wu model from MCPA and Wolff simulations: free-exponent and fixed-exponent fits
Vyacheslav Mozolenko, Ian Pile, Lev Shchur
Capillary Coarsening Drives Re-entrant Statistical Transitions in Early Coffee-Ring Growth
Arundas Chandradasan, Dileep Mampallil
Maximum entropy explanation for the ubiquity of power-law mechanical responses
Sverre Holm
Thermodynamic Bethe Ansatz for the Toda chain from inverse scattering transform
Alberto Brollo