scholarly journals Majority-vote model on spatially embedded networks: Crossover from mean-field to Ising universality classes

2016 ◽  
Vol 93 (5) ◽  
Author(s):  
C. I. N. Sampaio Filho ◽  
T. B. dos Santos ◽  
A. A. Moreira ◽  
F. G. B. Moreira ◽  
J. S. Andrade
2020 ◽  
Vol 93 (9) ◽  
Author(s):  
Andrzej Krawiecki

Abstract Ferromagnetic and spin-glass-like transitions in nonequilibrium spin models in contact with two thermal baths with different temperatures are investigated. The models comprise the Sherrington-Kirkpatrick model and the dilute spin glass model which are the Ising models on complete and random graphs, respectively, with edges corresponding, with certain probability, to positive and negative exchange integrals. The spin flip rates are combinations of two Glauber rates at the two temperatures, and by varying the coefficients of this combination probabilities of contact of the model with each thermal bath and thus the level of thermal noise in the model are changed. Particular attention is devoted to the majority vote model in which one of the two above-mentioned temperatures is zero and the other one tends to infinity. Only in rare cases such nonequilibrium models can be mapped onto equilibrium ones at certain effective temperature. Nevertheless, Monte Carlo simulations show that transitions from the paramagnetic to the ferromagnetic and spin-glass-like phases occur in all cases under study as the level of thermal noise is varied, and the phase diagrams resemble qualitatively those for the corresponding equilibrium models obtained with varying temperature. Theoretical investigation of the model on complete and random graphs is performed using the TAP equations as well as mean-field and pair approximations, respectively. In all cases theoretical calculations yield reasonably correct predictions concerning location of the phase border between the paramagnetic and ferromagnetic phases. In the case of the spin-glass-like transition only qualitative agreement between theoretical and numerical results is achieved using the TAP equations, and the mean-field and pair approximations are not suitable for the study of this transition. The obtained results can be interesting for modeling opinion formation by means of the majority-vote and related models and suggest that in the presence of negative interactions between agents, apart from the ferromagnetic phase corresponding to consensus formation, spin-glass-like phase can occur in the society characterized by local rather than long-range ordering. Graphical abstract


2017 ◽  
Vol 120 (1) ◽  
pp. 18003 ◽  
Author(s):  
Feng Huang ◽  
Hanshuang Chen ◽  
Chuansheng Shen

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Bartłomiej Nowak ◽  
Katarzyna Sznajd-Weron

We study two variants of the modified Watts threshold model with a noise (with nonconformity, in the terminology of social psychology) on a complete graph. Within the first version, a noise is introduced via so-called independence, whereas in the second version anticonformity plays the role of a noise, which destroys the order. The modified Watts threshold model, studied here, is homogeneous and possesses an up-down symmetry, which makes it similar to other binary opinion models with a single-flip dynamics, such as the majority-vote and the q-voter models. Because within the majority-vote model with independence only continuous phase transitions are observed, whereas within the q-voter model with independence also discontinuous phase transitions are possible, we ask the question about the factor, which could be responsible for discontinuity of the order parameter. We investigate the model via the mean-field approach, which gives the exact result in the case of a complete graph, as well as via Monte Carlo simulations. Additionally, we provide a heuristic reasoning, which explains observed phenomena. We show that indeed if the threshold r=0.5, which corresponds to the majority-vote model, an order-disorder transition is continuous. Moreover, results obtained for both versions of the model (one with independence and the second one with anticonformity) give the same results, only rescaled by the factor of 2. However, for r>0.5 the jump of the order parameter and the hysteresis is observed for the model with independence, and both versions of the model give qualitatively different results.


2017 ◽  
Vol 27 (8) ◽  
pp. 081102 ◽  
Author(s):  
Hanshuang Chen ◽  
Chuansheng Shen ◽  
Haifeng Zhang ◽  
Jürgen Kurths

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Jesus M. Encinas ◽  
Pedro E. Harunari ◽  
M. M. de Oliveira ◽  
Carlos E. Fiore

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
André L. M. Vilela ◽  
H. Eugene Stanley
Keyword(s):  

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 319 ◽  
Author(s):  
Franklin Tchakounté ◽  
Ahmadou Faissal ◽  
Marcellin Atemkeng ◽  
Achille Ntyam

Social networks play an important role in today’s society and in our relationships with others. They give the Internet user the opportunity to play an active role, e.g., one can relay certain information via a blog, a comment, or even a vote. The Internet user has the possibility to share any content at any time. However, some malicious Internet users take advantage of this freedom to share fake news to manipulate or mislead an audience, to invade the privacy of others, and also to harm certain institutions. Fake news seeks to resemble traditional media to establish its credibility with the public. Its seriousness pushes the public to share them. As a result, fake news can spread quickly. This fake news can cause enormous difficulties for users and institutions. Several authors have proposed systems to detect fake news in social networks using crowd signals through the process of crowdsourcing. Unfortunately, these authors do not use the expertise of the crowd and the expertise of a third party in an associative way to make decisions. Crowds are useful in indicating whether or not a story should be fact-checked. This work proposes a new method of binary aggregation of opinions of the crowd and the knowledge of a third-party expert. The aggregator is based on majority voting on the crowd side and weighted averaging on the third-party side. An experimentation has been conducted on 25 posts and 50 voters. A quantitative comparison with the majority vote model reveals that our aggregation model provides slightly better results due to weights assigned to accredited users. A qualitative investigation against existing aggregation models shows that the proposed approach meets the requirements or properties expected of a crowdsourcing system and a voting system.


2003 ◽  
Vol 67 (2) ◽  
Author(s):  
Paulo R. A. Campos ◽  
Viviane M. de Oliveira ◽  
F. G. Brady Moreira
Keyword(s):  

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