Link overlap influences opinion dynamics on multiplex networks: spin model approach (2106.13600v2)

Abstract: Consider a multiplex network formed by two layers indicating social interactions: the first layer is a friendship network and the second layer is a network of business relations. In this duplex network each pair of individuals can be connected in different ways: they can be connected by a friendship but not connected by a business relation, they can be connected by a business relation without being friends, or they can be simultaneously friends and in a business relation. In the latter case we say that the links in different layers overlap. These three types of connections are called multilinks and the multidegree indicates the sum of multilinks of a given type that are incident to a given node. Previous models of opinion formation on multilayer networks have mostly neglected the effect of link overlap. Here we show that link overlap can have important effects in opinion formation. Indeed, emerging pattern of opinion formation can be significantly influenced by the statistical properties of multilinks, and in particular by the multidegree distribution. To quantitatively address this problem, we study a simple spin model, called the Ashkin-Teller model including 2-body and 4-body interactions between nodes in different layers. Here we fully investigate the rich phase diagram of this model which includes a large variety of phase transitions (PTs). Indeed the phase digram or the model displays continuous, discontinuous, successive discontinuous, and hybrid PTs.