scholarly journals A gentle introduction to the minimal Naming Game

2016 ◽  
Vol 30 ◽  
pp. 171-192 ◽  
Author(s):  
Andrea Baronchelli

Social conventions govern countless behaviors all of us engage in every day, from how we greet each other to the languages we speak. But how can shared conventions emerge spontaneously in the absence of a central coordinating authority? The Naming Game model shows that networks of locally interacting individuals can spontaneously self-organize to produce global coordination. Here, we provide a gentle introduction to the main features of the model, from the dynamics observed in homogeneously mixing populations to the role played by more complex social networks, and to how slight modifications of the basic interaction rules give origin to a richer phenomenology in which more conventions can co-exist indefinitely.

2019 ◽  
Vol 30 (11) ◽  
pp. 1950094 ◽  
Author(s):  
Jianye Yu ◽  
Junjie Lv ◽  
Yuanzhuo Wang ◽  
Jingyuan Li

Information dissemination groups, especially those disseminating the same kind of information such as advertising, product promotion, etc., compete with each other when their information spread on social networks. Most of the existing methods analyze the dissemination mechanism mainly upon the information itself without considering human characteristics, e.g. relation networks, cooperation/defection, etc. In this paper, we introduce a framework of social evolutionary game (SEG) to investigate the influence of human behaviors in competitive information dissemination. Coordination game is applied to represent human behaviors in the competition of asynchronous information diffusion. We perform a series of simulations through a specific game model to analyze the mechanism and factors of information diffusion, and show that when the benefits of competitive information is around 1.2 times of the original one, it can compensate the loss of reputation caused by the change of strategy. Furthermore, through experiments on a dataset of two films on Sina Weibo, we described the mechanism of competition evolution over real data of social network, and validated the effectiveness of our model.


2012 ◽  
Vol 86 (3) ◽  
Author(s):  
Suman Kalyan Maity ◽  
T. Venkat Manoj ◽  
Animesh Mukherjee

2015 ◽  
Vol 727-728 ◽  
pp. 969-975
Author(s):  
Min Li ◽  
Rui Qiu Ou ◽  
Yan Ling Song

As a medium forcommunication and coalition, social network plays an important role in economicactivities. Empirical researches indicate that most of social networks performsignificant small-world characteristics, so this paper assumes the socialnetwork among merchants is a small-world network, and then studies the agencyactivities of merchants by means of simulation based on a game model. We findthat if the average degree of the network increases, the wage of agents willdecrease and social efficiency will increase, but the probability of emergenceof third-part institutions such as courts, which is the basis of modern marketeconomy, will decrease.


2020 ◽  
Vol 384 (35) ◽  
pp. 126908
Author(s):  
Xue Yang ◽  
Zhiliang Zhu ◽  
Hai Yu ◽  
Yuli Zhao ◽  
Ying Wang

2020 ◽  
Vol 102 ◽  
pp. 14-29 ◽  
Author(s):  
Eric Ke Wang ◽  
Chien-Ming Chen ◽  
Siu Ming Yiu ◽  
Mohammad Mehedi Hassan ◽  
Majed Alrubaian ◽  
...  

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Xue Yang ◽  
Zhiliang Zhu ◽  
Hai Yu ◽  
Yuli Zhao

We study herein the problem of the location of the information propagation source in social networks based on the network topology and a set of observations. We propose a concise and novel method to accurately locate the source of information using naming game theory. This study introduces the design of a dynamic deployment method that reduces considerably the number of observations and the time needed to locate the source. Moreover, it calculates the probability of each node that acts as a source based on the information provided by observations. This method can be potentially applied to various information propagation models. The simulation results reveal that the method is able to estimate the information source within a small number of hops from the true source.


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