Gossip-Based Model for Opinion Dynamics with Probabilistic Group Interactions

Abstract

Classical models of opinion dynamics utilize deterministic methods to describe how opinions evolve within a social network. More recent models are shifting towards randomized processes to emulate real-world interactions. These include gossip-based models that use pairwise interactions to represent the opinion formation process. In this paper, we propose to extend the gossip-based models for opinion dynamics by allowing group interactions with randomly selected participants.