Non-consensus opinion models on complex networks
Qian Li, Lidia A. Braunstein, Huijuan Wang, Jia Shao, H. Eugene, Stanley, Shlomo Havlin

TL;DR
This paper extends non-consensus opinion models on complex networks by introducing a weight factor and studying coupled networks, revealing how interdependent links influence phase transitions and opinion consensus.
Contribution
It introduces the NCOW model with a weight factor, analyzes the impact of interdependent links on opinion dynamics, and demonstrates transition from second-order to hybrid and abrupt phase transitions.
Findings
Increasing weight W stabilizes minority opinion clusters.
Interdependent links induce a shift from second-order to hybrid and abrupt phase transitions.
Coupled networks can lead to consensus opinions due to interdependent interactions.
Abstract
We focus on non-consensus opinion models in which above a certain threshold two opinions coexist in a stable relationship. We revisit and extend the non-consensus opinion (NCO) model introduced by Shao. We generalize the NCO model by adding a weight factor W to individual's own opinion when determining its future opinion (NCOW model). We find that as W increases the minority opinion holders tend to form stable clusters with a smaller initial minority fraction compared to the NCO model. We also revisit another non-consensus opinion, the inflexible contrarian opinion (ICO) model, which introduces inflexible contrarians to model a competition between two opinions in the steady state. In the ICO model, the inflexible contrarians effectively decrease the size of the largest cluster of the rival opinion. All of the above models have previously been explored in terms of a single network.…
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