Voter model on adaptive networks

Abstract

Voter model is an important basic model in statistical physics. In recent years, it has been more and more used to describe the process of opinion formation in sociophysics. In real complex systems, the interactive network of individuals is dynamically adjusted, and the evolving network topology and individual behaviors affect each other. Therefore, we propose a linking dynamics to describe the coevolution of network topology and individual behaviors in this paper, and study the voter model on the adaptive network. We theoretically analyze the properties of the voter model, including consensus probability and time. The evolution of opinions on dynamic networks is further analyzed from the perspective of evolutionary game. Finally, a case study of real data is shown to verify the effectiveness of the theory.

Research on Opinion Dynamics on Social Networks

“…Therefore, regardless of the focused node's prior state, the possibility that the next picked node will have a positive spin is higher if the focal node's positive spins are greater than the negative spins. The node's future state, as determined by this update rule, is unrelated to its initial state [23] . Voter models offer a wide variety of practical uses.…”

“…Due to the connection of these two processes, nodes and links can grow concurrently, a phenomenon that illustrates how people's beliefs influence how they link and how their new ties are formed. Understanding the evolution of opinion in dynamic networks is crucial [50] .…”