Consensus formation on a triad scale-free network

TL;DR

This paper extends the Sznajd model to a triad scale-free network, incorporating multiple opinions and convincing probabilities, resulting in vote distributions that closely match real-world data.

Contribution

It introduces a more realistic network structure and multiple opinions into the Sznajd model, enhancing its applicability to real social dynamics.

Findings

Network clustering increases opinion consensus realism

Multiple opinions lead to more accurate vote distributions

Convincing probability affects opinion spread dynamics

Abstract

Several cases of the Sznajd model of socio-physics, that only a group of people sharing the same opinion can convince their neighbors, have been simulated on a more realistic network with a stronger clustering. In addition, many opinions, instead of usually only two, and a convincing probability have been also considered. Finally, with minor changes we obtain a vote distribution in good agreement with reality.