scholarly journals Bounded Confidence Gossip Algorithms for Opinion Formation and Data Clustering

2019 ◽  
Vol 64 (3) ◽  
pp. 1150-1155 ◽  
Author(s):  
Linh Thi Hoai Nguyen ◽  
Takayuki Wada ◽  
Izumi Masubuchi ◽  
Toru Asai ◽  
Yasumasa Fujisaki
Keyword(s):  
Data Clustering ◽  
Opinion Formation ◽  
Gossip Algorithms ◽  
Bounded Confidence

Opinion formation under bounded confidence via gossip algorithms

2015 ◽  
Author(s):  
Nguyen Thi Hoai Linh ◽  
Takayuki Wada ◽  
Izumi Masubuchi ◽  
Toru Asai ◽  
Yasumasa Fujisaki
Keyword(s):  
Opinion Formation ◽  
Gossip Algorithms ◽  
Bounded Confidence

scholarly journals The Combination of Pairwise and Group Interactions Promotes Consensus in Opinion Dynamics

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiaoxuan Liu ◽  
Changwei Huang ◽  
Haihong Li ◽  
Qionglin Dai ◽  
Junzhong Yang
Keyword(s):  
Complex Systems ◽  
Numerical Simulations ◽  
Complete Graph ◽  
Group Interaction ◽  
Opinion Dynamics ◽  
Pairwise Interaction ◽  
Network Structures ◽  
Opinion Formation ◽  
Group Interactions ◽  
Bounded Confidence

In complex systems, agents often interact with others in two distinct types of interactions, pairwise interaction and group interaction. The Deffuant–Weisbuch model adopting pairwise interaction and the Hegselmann–Krause model adopting group interaction are the two most widely studied opinion dynamics. In this study, we propose a novel opinion dynamics by combining pairwise and group interactions for agents and study the effects of the combination on consensus in the population. In the model, we introduce a parameter α to control the weights of the two interactions in the dynamics. Through numerical simulations, we find that there exists an optimal α , which can lead to a highest probability of complete consensus and minimum critical bounded confidence for the formation of consensus. Furthermore, we show the effects of α on opinion formation by presenting the observations for opinion clusters. Moreover, we check the robustness of the results on different network structures and find the promotion of opinion consensus by α not limited to a complete graph.

scholarly journals OPINION FORMATION MODELS BASED ON GAME THEORY

2007 ◽  
Vol 18 (09) ◽  
pp. 1377-1395 ◽  
Author(s):  
ALESSANDRO DI MARE ◽  
VITO LATORA
Keyword(s):  
Game Theory ◽  
Numerical Simulations ◽  
Opinion Dynamics ◽  
Strategic Game ◽  
Opinion Formation ◽  
Bounded Confidence ◽  
Formation Dynamics ◽  
Bounded Confidence Model

A way to simulate the basic interactions between two individuals with different opinions, in the context of strategic game theory, is proposed. Various games are considered, which produce different kinds of opinion formation dynamics. First, by assuming that all individuals (players) are equals, we obtain the bounded confidence model of continuous opinion dynamics proposed by Deffuant et al. In such a model a tolerance threshold is defined, such that individuals with difference in opinion larger than the threshold can not interact. Then, we consider that the individuals have different inclinations to change opinion and different abilities in convincing the others. In this way, we obtain the so-called "Stubborn individuals and Orators" (SO) model, a generalization of the Deffuant et al. model, in which the threshold tolerance is different for every couple of individuals. We explore, by numerical simulations, the dynamics of the SO model, and we propose further generalizations that can be implemented.

scholarly journals Opinion formation with time-varying bounded confidence

PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0172982 ◽  
Author(s):  
YunHong Zhang ◽  
QiPeng Liu ◽  
SiYing Zhang
Keyword(s):  
Time Varying ◽  
Opinion Formation ◽  
Bounded Confidence

scholarly journals Dynamics of linguistic opinion formation in bounded confidence model

2016 ◽  
Vol 32 ◽  
pp. 52-61 ◽  
Author(s):  
Yucheng Dong ◽  
Xia Chen ◽  
Haiming Liang ◽  
Cong-Cong Li
Keyword(s):  
Opinion Formation ◽  
Bounded Confidence ◽  
Bounded Confidence Model

BOUNDED CONFIDENCE MODEL IN COMPLEX NETWORKS

2013 ◽  
Vol 24 (08) ◽  
pp. 1350049 ◽  
Author(s):  
K. FELIJAKOWSKI ◽  
R. KOSINSKI
Keyword(s):  
Complex Networks ◽  
Numerical Simulations ◽  
Formation Process ◽  
Order Parameter ◽  
Hierarchical Network ◽  
Opinion Formation ◽  
Spreading Process ◽  
Bounded Confidence ◽  
Initial Source ◽  
Bounded Confidence Model

This paper presents a study of the bounded confidence model applied to the complex networks. Two different cases were examined: opinion formation process in the Barabási–Albert network and corruption spreading in a hierarchical network. For both cases, the value of the bounded confidence parameter ε was assumed as a constant, or its value was dependent on the degree of a node in the network. To measure the opinion formation and corruption spreading processes, we introduced the order parameter related to the number of interfaces in the system. As a results of numerical simulations, the influence of the values of ε on the final opinions in the population, as well as, the influence of an initial source of corruption in the company structure on the corruption spreading process, were obtained and discussed.

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