scholarly journals Majority-Vote Model on Scale-Free Hypergraphs

2015 ◽  
Vol 127 (3a) ◽  
pp. A-55-A-58 ◽  
Author(s):  
T. Gradowski ◽  
A. Krawiecki
Keyword(s):  
2020 ◽  
Vol 10 (1) ◽  
Author(s):  
André L. M. Vilela ◽  
Bernardo J. Zubillaga ◽  
Chao Wang ◽  
Minggang Wang ◽  
Ruijin Du ◽  
...  

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):  

2013 ◽  
Vol 24 (11) ◽  
pp. 1350083 ◽  
Author(s):  
F. W. S. LIMA

We study a nonequilibrium model with up-down symmetry and a noise parameter q known as majority-vote model (MVM) of [M. J. Oliveira, J. Stat. Phys.66, 273 (1992)] with heterogeneous agents on square lattice (SL). By Monte Carlo (MC) simulations and finite-size scaling relations, the critical exponents β∕ν, γ∕ν and 1∕ν and points qc and U* are obtained. After extensive simulations, we obtain β∕ν = 0.35(1), γ∕ν = 1.23(8) and 1∕ν = 1.05(5). The calculated values of the critical noise parameter and Binder cumulant are qc = 0.1589(4) and U* = 0.604(7). Within the error bars, the exponents obey the relation 2β∕ν + γ∕ν = 2 and the results presented here demonstrate that the MVM heterogeneous agents belongs to a different universality class than the nonequilibrium MVM with homogeneous agents on SL.


1992 ◽  
Vol 66 (1-2) ◽  
pp. 273-281 ◽  
Author(s):  
M. J. de Oliveira

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