opinion dynamics
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Automatica ◽  
2022 ◽  
Vol 137 ◽  
pp. 110138
Rongrong Kang ◽  
Xiang Li

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 105
Robert Jankowski ◽  
Anna Chmiel

Modelling the epidemic’s spread on multiplex networks, considering complex human behaviours, has recently gained the attention of many scientists. In this work, we study the interplay between epidemic spreading and opinion dynamics on multiplex networks. An agent in the epidemic layer could remain in one of five distinct states, resulting in the SIRQD model. The agent’s attitude towards respecting the restrictions of the pandemic plays a crucial role in its prevalence. In our model, the agent’s point of view could be altered by either conformism mechanism, social pressure, or independent actions. As the underlying opinion model, we leverage the q-voter model. The entire system constitutes a coupled opinion–dynamic model where two distinct processes occur. The question arises of how to properly align these dynamics, i.e., whether they should possess equal or disparate timescales. This paper highlights the impact of different timescales of opinion dynamics on epidemic spreading, focusing on the time and the infection’s peak.

2022 ◽  
Vol 12 (1) ◽  
Bernardo J. Zubillaga ◽  
André L. M. Vilela ◽  
Minggang Wang ◽  
Ruijin Du ◽  
Gaogao Dong ◽  

AbstractIn this work, we study the opinion dynamics of the three-state majority-vote model on small-world networks of social interactions. In the majority-vote dynamics, an individual adopts the opinion of the majority of its neighbors with probability 1-q, and a different opinion with chance q, where q stands for the noise parameter. The noise q acts as a social temperature, inducing dissent among individual opinions. With probability p, we rewire the connections of the two-dimensional square lattice network, allowing long-range interactions in the society, thus yielding the small-world property present in many different real-world systems. We investigate the degree distribution, average clustering coefficient and average shortest path length to characterize the topology of the rewired networks of social interactions. By employing Monte Carlo simulations, we investigate the second-order phase transition of the three-state majority-vote dynamics, and obtain the critical noise $$q_c$$ q c , as well as the standard critical exponents $$\beta /\nu$$ β / ν , $$\gamma /\nu$$ γ / ν , and $$1/\nu$$ 1 / ν for several values of the rewiring probability p. We conclude that the rewiring of the lattice enhances the social order in the system and drives the model to different universality classes from that of the three-state majority-vote model in two-dimensional square lattices.

Sushmitha Shree S ◽  
Kishore G V ◽  
Avhishek Chatterjee ◽  
Krishna Jagannathan

2022 ◽  
Vol 21 (1) ◽  
pp. 1-32
Abigail Hickok ◽  
Yacoub Kureh ◽  
Heather Z. Brooks ◽  
Michelle Feng ◽  
Mason A. Porter

2022 ◽  
Vol 7 (4) ◽  
pp. 5616-5633
Rebecca C. Tyson ◽  
Noah D. Marshall ◽  
Bert O. Baumgaertner ◽  

<abstract><p>Public opinion and opinion dynamics can have a strong effect on the transmission rate of an infectious disease for which there is no vaccine. The coupling of disease and opinion dynamics however, creates a dynamical system that is complex and poorly understood. We present a simple model in which susceptible groups adopt or give up prophylactic behaviour in accordance with the influence related to pro- and con-prophylactic communication. This influence varies with disease prevalence. We observe how the speed of the opinion dynamics affects the total size and peak size of the epidemic. We find that more reactive populations will experience a lower peak epidemic size, but possibly a larger final size and more epidemic waves, and that an increase in polarization results in a larger epidemic.</p></abstract>

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