Large-scale events such as political scandals or misinformation campaigns can abruptly shift the collective opinion of a population and reshape the dynamics in ways that standard local-interaction models of sociophysics do not capture. Here, we investigate the dynamics of opinion formation when a group of interacting a...
Abstract. We analyze a stochastic model for the diffusion of two competing opinions in a population composed of trend-followers, opposers, and indifferent individuals. The model introduces a reinforcement mechanism modulated by parameters representing these behavioral types, resulting in a rich asymptotic structure. W...
We study a nonlinear opinion dynamics model for stubborn individuals in time-varying signed cooperation–competition networks. The model incorporates nonlinear response functions, stochastic perturbations, and memory effects within a unified dynamical framework. We establish a uniform boundedness result under bounded ex...
Opinion dynamics have been studied for decades across disciplines, with much of the theoretical literature focusing on behaviors such as consensus, polarization, and clustering. Although classic models can exhibit more complex opinion patterns in simulations, quantifying such distributions is not fully understood. To a...
Various theoretical and empirical studies have accounted for why humans cooperate in competitive environments. Although prior work has revealed that network structure and multiplex interactions can promote cooperation, most theory assumes that individuals play dilemma games in all social contexts. However, real-world a...
A novel framework for modeling binary opinions of individuals connected through a weighted directed network, where edge weights quantify interpersonal influence is proposed, which allows individuals to update their biases using structured memory sets that capture limited and delayed information exchange.
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