scholarly journals Significant Role of Trust and Distrust in Social Simulation

2021 ◽  
Author(s):  
Akira Ishii ◽  
Yasuko Kawahata ◽  
Nozomi Okano

This paper introduces the Trust-Distrust Model and its applications, extending the Bounded Confidence Model, a theory of opinion dynamics, to include the relationship between trust and mistrust. In recent years, there has been an increase in the number of cases in which the prerequisites for conventional communication (e.g., the other person’s gender, appearance, tone of voice, etc.) cannot be established without the exchange of personal information. However, in recent years, there has been an increase in the use of personal information, such as letters and pictograms “as cryptographic asset data” for two-way communication. However, there are advantages and disadvantages to using information assets in the form of personalized data, which are excerpts of personal information as described above. In the future, the discussion of trust value in the above data will accelerate in indicators such as personal credit scoring. In this paper, the Trust-Distrust Model will be discussed with respect to theories that also address charismatic people, the effects of advertising, and social divisions. Furthermore, simulations of the Trust-Distrust Model show that 55% agreement is sufficient to build social consensus. By addressing this theory, we hope to use it to discuss and predict social risk in future credit scoring discussions.

Automatica ◽  
2021 ◽  
Vol 129 ◽  
pp. 109683
Author(s):  
Francesco Vasca ◽  
Carmela Bernardo ◽  
Raffaele Iervolino

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiaoxuan Liu ◽  
Changwei Huang ◽  
Haihong Li ◽  
Qionglin Dai ◽  
Junzhong Yang

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.


2017 ◽  
Vol 62 (11) ◽  
pp. 5678-5693 ◽  
Author(s):  
Francois Baccelli ◽  
Avhishek Chatterjee ◽  
Sriram Vishwanath

2007 ◽  
Vol 18 (09) ◽  
pp. 1377-1395 ◽  
Author(s):  
ALESSANDRO DI MARE ◽  
VITO LATORA

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.


2011 ◽  
Vol 271-273 ◽  
pp. 1286-1290
Author(s):  
Yan Feng Guo ◽  
Na Sun ◽  
Yuan Yao

Credit risk problem is an essential problem in financial management area. People usually employ personal credit scoring to avoid financial risk problem. Although many methods have been proposed for evaluating the personal credit scoring and obtained good effects, most of these methods were called single model types, which would be disturbed by model self-parameter, data noise and other external factors. In order to overcome the weakness of single model, we believe one of best ways is to construct an ensemble model. In this paper, we proposed a new style of ensemble model and employed two public credit datasets to certify the validity of our ensemble model. The experimental result shows that the ensemble SOM-SVM model can overcome the single model weakness and improve the accuracy of classification, which is good for constructing a better credit scoring system in future.


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