scholarly journals Convergence to global consensus in opinion dynamics under a nonlinear voter model

2012 ◽  
Vol 376 (4) ◽  
pp. 282-285 ◽  
Author(s):  
Han-Xin Yang ◽  
Wen-Xu Wang ◽  
Ying-Cheng Lai ◽  
Bing-Hong Wang
2014 ◽  
Vol 25 (07) ◽  
pp. 1450022 ◽  
Author(s):  
Saijun Chen ◽  
Haibo Hu ◽  
Jun Chen ◽  
Zhigao Chen

There exist scaling correlations between the edge weights and the nodes' degrees in weighted social networks. Based on the empirical findings, we study a multi-state voter model on weighted social networks where the weight is given by the product of agents' degrees raised to a power θ and there exist persistent individuals whose opinions are independent of those of their friends. We find that the fraction of each opinion will converge to a value which only relates to the degrees of initial committed agents and the scaling exponent θ. The analytical predictions are verified by numerical simulations. The model indicates that agents' degrees and scaling exponent can significantly influence the final coexistence or consensus state of opinions. We also study the influence of degree mixing characteristics on the dynamics model by numerical simulations and discuss the relation between the model and the other related opinion dynamics models on social networks with different topological structures and initial configurations.


2011 ◽  
Vol 22 (01) ◽  
pp. 51-62 ◽  
Author(s):  
FEI XIONG ◽  
YUN LIU ◽  
ZHENJIANG ZHANG

Based on the voter model, we present a new opinion formation model which takes into account the evolution of both opinions and individual inclinations. A memory-based inclination is developed gradually during the process of social interaction; however, if the individual inclination gets strong enough, it will react to opinion dynamics. We assume that an individual inclination increases with the number of times the individual has held its most frequent opinion in the past interactions. As a result of inclination choices the transition rate following neighbors decreases, thus slowing down the microscopic dynamics. Analytical and simulation results indicate the system under the action of opinion inclinations evolves to a more polarized state for average opinion. The appearance of extremists holding the minority opinion is observed in the final state, where one opinion predominates. It is also found that the stable opinion and relaxation time depend on network topology and memory length. Moreover, this model is not only valid to the voter model, but can also be applied to other spin systems.


Author(s):  
Didier A. Vega-Oliveros ◽  
Helder L. C. Grande ◽  
Flavio Iannelli ◽  
Federico Vazquez
Keyword(s):  

2009 ◽  
Vol 80 (4) ◽  
Author(s):  
Han-Xin Yang ◽  
Zhi-Xi Wu ◽  
Changsong Zhou ◽  
Tao Zhou ◽  
Bing-Hong Wang

2015 ◽  
Vol 18 (01n02) ◽  
pp. 1550002 ◽  
Author(s):  
MEYSAM ALIZADEH ◽  
CLAUDIO CIOFFI-REVILLA ◽  
ANDREW CROOKS

Empirical findings from social psychology show that sometimes people show favoritism toward in-group members in order to reach a global consensus, even against individuals' own preferences (e.g., altruistically or deontically). Here we integrate ideas and findings on in-group favoritism, opinion dynamics, and radicalization using an agent-based model entitled cooperative bounded confidence (CBC). We investigate the interplay of homophily, rejection, and in-group cooperation drivers on the formation of opinion clusters and the emergence of extremist, radical opinions. Our model is the first to explicitly explore the effect of in-group favoritism on the macro-level, collective behavior of opinions. We compare our model against the two-dimentional bounded confidence model with rejection mechanism, proposed by Huet et al. [Adv. Complex Syst.13(3) (2010) 405–423], and find that the number of opinion clusters and extremists is reduced in our model. Moreover, results show that group influence can never dominate homophilous and rejecting encounters in the process of opinion cluster formation. We conclude by discussing implications of our model for research on collective behavior of opinions emerging from individuals' interaction.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bartłomiej Nowak ◽  
Bartosz Stoń ◽  
Katarzyna Sznajd-Weron

AbstractWe introduce a generalized version of the noisy q-voter model, one of the most popular opinion dynamics models, in which voters can be in one of $$s \ge 2$$ s ≥ 2 states. As in the original binary q-voter model, which corresponds to $$s=2$$ s = 2 , at each update randomly selected voter can conform to its q randomly chosen neighbors only if they are all in the same state. Additionally, a voter can act independently, taking a randomly chosen state, which introduces disorder to the system. We consider two types of disorder: (1) annealed, which means that each voter can act independently with probability p and with complementary probability $$1-p$$ 1 - p conform to others, and (2) quenched, which means that there is a fraction p of all voters, which are permanently independent and the rest of them are conformists. We analyze the model on the complete graph analytically and via Monte Carlo simulations. We show that for the number of states $$s>2$$ s > 2 the model displays discontinuous phase transitions for any $$q>1$$ q > 1 , on contrary to the model with binary opinions, in which discontinuous phase transitions are observed only for $$q>5$$ q > 5 . Moreover, unlike the case of $$s=2$$ s = 2 , for $$s>2$$ s > 2 discontinuous phase transitions survive under the quenched disorder, although they are less sharp than under the annealed one.


2009 ◽  
Vol 20 (05) ◽  
pp. 677-686 ◽  
Author(s):  
KE HU ◽  
YI TANG

We develop a consensus model for studying opinion dynamics in weighted networks and investigate the effects of both the distribution of weights and the correlations between weight and degree on dynamical behaviors of opinion formation. Our results suggest that a global consensus in the weighted networks to reach is more difficult than that in unweighted network, and strongly depends on the heterogeneity of connection strengths. In addition, in the weighted network with very large heterogeneity of connection strengths, only single macroscopic opinion cluster can be formed, which differs from the behavior in the unweighted network where the next-largest macroscopic opinion cluster may exist.


2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Zhen Wang ◽  
Yi Liu ◽  
Lin Wang ◽  
Yan Zhang ◽  
Zhen Wang

2017 ◽  
Vol 96 (5) ◽  
Author(s):  
Pascal P. Klamser ◽  
Marc Wiedermann ◽  
Jonathan F. Donges ◽  
Reik V. Donner
Keyword(s):  

2014 ◽  
Vol 17 (03n04) ◽  
pp. 1450012 ◽  
Author(s):  
SHUANGLING LUO ◽  
HAOXIANG XIA ◽  
BORUI YIN

In this paper, an agent-based model for opinion dynamics on an adaptive coupled random network is proposed. Based on Festinger's idea of "cognitive dissonance", in the proposed model an agent can either make opinion exchange with a neighbor according to the bounded confidence mechanism, or migrate toward another network position in case that the majority of the adjacent agents are beyond the confidence bound. Through numerical simulations, we test how the key factors, such as the interconnectivity of the two communities, the confidence bound or the communal tolerance to diversity, the initial distributions of the opinions, and the level of sense of community, affect the final opinion state of the system. The overall analyses show a general picture of the dynamics of opinions on an adaptive network with community structure. In particular, the results reveal that the clustering of similar agents has a bifurcating function for the opinion dynamics. Given that the inter-communal influence is high, the clustering fosters the global consensus. If the inter-communal influence is weak, the clustering would instead intensify polarization and thus hinder the formation of global consensus. The factors of the communal tolerances and interconnectivity leverage the bifurcating effect.


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