Theory of Opinion Distribution in Human Relations Where Trust and Distrust Mixed

Ishii, Akira; Kawahata, Yasuko

doi:10.1007/978-981-15-5925-9_40

Cited by 5 publications

(6 citation statements)

References 6 publications

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“…Ishii and Kawahata have shown that if more than 55% of the N 2 D ij are positive, that is, trustworthy, the system will form a consensus [17]. This result is also true for random networks [26].…”

Section: Opinion Dynamics Including Both Trust and Distrustmentioning

confidence: 82%

Significant Role of Trust and Distrust in Social Simulation

Ishii¹,

Kawahata²,

Okano³

2023

The Psychology of Trust

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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.

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Section: Opinion Dynamics Including Both Trust and Distrustmentioning

confidence: 82%

Significant Role of Trust and Distrust in Social Simulation

Ishii¹,

Kawahata²,

Okano³

2023

The Psychology of Trust

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“…Those uncertainties of the estimates are going to be studied as the next step of the research project. Hence, in subsequent studies, we will run several model realizations to check the robustness of trust threshold [31,32] and other related articles [21,30].…”

Section: Discussionmentioning

confidence: 99%

“…In a given scale-free network, a "hub" person maintains strong influence within a network, that is, each scale-free network is determined by the hub's opinion and hence unique: it is difficult to identify the general characteristics of the scale-free network from its uniqueness. Let us inform Ishii's opinion dynamics model calculations with a scale-free network have already been done elsewhere [21,30]. Hence, calculations using the scale-free network are technically feasible for us; however, because of the aforementioned reason, a scale-free network is not adopted in this study.…”

Section: Setting Of Social Simulation Calculationmentioning

confidence: 99%

“…As shown in Figure 3, opinions converge within an in-group, and a consensus is formed when a degree of trust among the people who belong to the in-group posits a positive value. Our calculation shows that when coefficient D is higher than 55%, an in-group forms a consensus [21,30]. Since this result can be applied to any of the two coexisting in-groups, we can assume consensus will be built when the degree of trust among members of an in-group is higher than 55%.…”

Section: Setting Of Social Simulation Calculationmentioning

confidence: 99%

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Social Simulation of Intergroup Conflicts Using a New Model of Opinion Dynamics

2021

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The social identity theory proposed by Tajfel et al. provides insight into how group membership and self-categorization cause intergroup prejudice and discrimination, finally leading to social conflicts. However, unanswered questions remain: under what conditions can an “in-group” and an “out-group” transform conflictual intergroup behavior into a more harmonious relationship and avoid social conflict? Opinion dynamics theory and social simulation are appropriate methods to answer this question. In this study, a new model of opinion dynamics proposed by Ishii is adopted, and we conduct simulations of intergroup conflicts. The new model, along with social simulations, presents how an in-group and an out-group can develop social harmony and avoid social conflict. According to our simulations, when the two groups trust their members 100%, the opinion inside an in-group converges. However, intragroup opinion diverges as trust within the group gets lower. On the other hand, intergroup opinion converges when the intergroup trust is higher than 50%. If intergroup trust is higher than 80%, then the intergroup opinions of the two perfectly overlap. Furthermore, if intragroup trust is 70% and intergroup trust is as low as 50%, the two groups' opinions completely polarize. We also calculated additional cases where intragroup trust was fixed at 70%, but for one-third of an in-group member trust an out-group with various values. Finally, a method to avoid further social crises can be obtained by examining real-world cases of partisan conflicts in recent America.

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“…In fact, trust has already been incorporated into opinion dynamics models (e.g., in Refs. [174][175][176][177][178][179][180][181][182]. However, even a cursory review of the literature on trust shows its complex nature.…”

Section: Trust and Involvementmentioning

confidence: 99%

Whither Now, Opinion Modelers?

Sobkowicz

2020

Front. Phys.

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Theory of Opinion Distribution in Human Relations Where Trust and Distrust Mixed

Cited by 5 publications

References 6 publications

Significant Role of Trust and Distrust in Social Simulation

Significant Role of Trust and Distrust in Social Simulation

Social Simulation of Intergroup Conflicts Using a New Model of Opinion Dynamics

Whither Now, Opinion Modelers?

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