scholarly journals CONTINUOUS OPINION DYNAMICS UNDER BOUNDED CONFIDENCE: A SURVEY

2007 ◽  
Vol 18 (12) ◽  
pp. 1819-1838 ◽  
Author(s):  
JAN LORENZ
Keyword(s):  
Social Psychology ◽  
Homogeneous Model ◽  
Opinion Dynamics ◽  
Complexity Science ◽  
Bifurcation Diagrams ◽  
Agent Based ◽  
Open Questions ◽  
Bounded Confidence ◽  
Cluster Configuration ◽  
Continuous Opinions

Models of continuous opinion dynamics under bounded confidence have been presented independently by Krause and Hegselmann and by Deffuant et al. in 2000. They have raised a fair amount of attention in the communities of social simulation, sociophysics and complexity science. The researchers working on it come from disciplines such as physics, mathematics, computer science, social psychology and philosophy. In these models agents hold continuous opinions which they can gradually adjust if they hear the opinions of others. The idea of bounded confidence is that agents only interact if they are close in opinion to each other. Usually, the models are analyzed with agent-based simulations in a Monte Carlo style, but they can also be reformulated on the agent's density in the opinion space in a master equation style. The contribution of this survey is fourfold. First, it will present the agent-based and density-based modeling frameworks including the cases of multidimensional opinions and heterogeneous bounds of confidence. Second, it will give the bifurcation diagrams of cluster configuration in the homogeneous model with uniformly distributed initial opinions. Third, it will review the several extensions and the evolving phenomena which have been studied so far, and fourth it will state some open questions.

THE EFFECT OF IN-GROUP FAVORITISM ON THE COLLECTIVE BEHAVIOR OF INDIVIDUALS' OPINIONS

2015 ◽  
Vol 18 (01n02) ◽  
pp. 1550002 ◽  
Author(s):  
MEYSAM ALIZADEH ◽  
CLAUDIO CIOFFI-REVILLA ◽  
ANDREW CROOKS
Keyword(s):  
Collective Behavior ◽  
Cluster Formation ◽  
Opinion Dynamics ◽  
Agent Based ◽  
Global Consensus ◽  
Group Cooperation ◽  
Bounded Confidence ◽  
Rejection Mechanism ◽  
Group Members ◽  
Bounded Confidence Model

Empirical findings from social psychology show that sometimes people show favoritism toward in-group members in order to reach a global consensus, even against individuals' own preferences (e.g., altruistically or deontically). Here we integrate ideas and findings on in-group favoritism, opinion dynamics, and radicalization using an agent-based model entitled cooperative bounded confidence (CBC). We investigate the interplay of homophily, rejection, and in-group cooperation drivers on the formation of opinion clusters and the emergence of extremist, radical opinions. Our model is the first to explicitly explore the effect of in-group favoritism on the macro-level, collective behavior of opinions. We compare our model against the two-dimentional bounded confidence model with rejection mechanism, proposed by Huet et al. [Adv. Complex Syst.13(3) (2010) 405–423], and find that the number of opinion clusters and extremists is reduced in our model. Moreover, results show that group influence can never dominate homophilous and rejecting encounters in the process of opinion cluster formation. We conclude by discussing implications of our model for research on collective behavior of opinions emerging from individuals' interaction.

scholarly journals A Survey on Nonstrategic Models of Opinion Dynamics

Games ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 65
Author(s):  
Michel Grabisch ◽  
Agnieszka Rusinowska
Keyword(s):  
Threshold Model ◽  
Opinion Dynamics ◽  
Time Varying ◽  
Binary Variable ◽  
Rule Model ◽  
Bounded Confidence ◽  
Degroot Model ◽  
Voter Models ◽  
Time Varying Models ◽  
Continuous Opinions

The paper presents a survey on selected models of opinion dynamics. Both discrete (more precisely, binary) opinion models as well as continuous opinion models are discussed. We focus on frameworks that assume non-Bayesian updating of opinions. In the survey, a special attention is paid to modeling nonconformity (in particular, anticonformity) behavior. For the case of opinions represented by a binary variable, we recall the threshold model, the voter and q-voter models, the majority rule model, and the aggregation framework. For the case of continuous opinions, we present the DeGroot model and some of its variations, time-varying models, and bounded confidence models.

Measuring the role of two competing groups of informed agents in opinion formation

SIMULATION ◽  
2018 ◽  
Vol 95 (8) ◽  
pp. 753-766
Author(s):  
Kamal S Selim ◽  
Ahmed E Okasha ◽  
Fatma R Farag
Keyword(s):  
Opinion Dynamics ◽  
The Other ◽  
Social Characteristics ◽  
Opinion Formation ◽  
Agent Based ◽  
Bounded Confidence ◽  
Significant Difference ◽  
The Impact ◽  
Bounded Confidence Model

For politicians, to promote intended messages to different groups of individuals, they could employ strategic individuals called “informed agents.” The aim of this article is to explore and measure the impact of two competing groups of informed agents on opinion dynamics within a society exposed to two extreme opinions. Thus, an agent-based model is developed as an extension to the bounded confidence model by assuming the existence of two groups of informed agents. The impact of these agents with respect to their social characteristics, such as, their size in the society, how tolerant they are, their self-weight and attitudes about others’ opinions is explored. Different assumptions about the initial opinion distributions and their effect are also investigated. Due to the difficulty of observing a real society, social simulation experiments are constructed based on artificial societies.The simulations conducted resulted in some interesting findings. With no dominating group of the two informed agents, the society will be ended up concentrated around a moderate position. On the other hand, with significant difference between the two group sizes, the larger group will polarize the population towards its opinion. However, this conclusion will not apply if the population is skewed towards the other opinion. In such case, the larger group will only succeed to turn some of the society to be more moderate. In a society skewed towards extreme opinion, dominant informed agents adopting the other extreme will not be able to shift the society towards their opinion. Finally, in radical societies informed agents could turn most of the society to be extremists.

CONTINUOUS OPINION DYNAMICS ON AN ADAPTIVE COUPLED RANDOM NETWORK

2014 ◽  
Vol 17 (03n04) ◽  
pp. 1450012 ◽  
Author(s):  
SHUANGLING LUO ◽  
HAOXIANG XIA ◽  
BORUI YIN
Keyword(s):  
Random Network ◽  
Opinion Dynamics ◽  
Confidence Bound ◽  
Key Factors ◽  
General Picture ◽  
Agent Based ◽  
Global Consensus ◽  
Proposed Model ◽  
Bounded Confidence ◽  
Initial Distributions

In this paper, an agent-based model for opinion dynamics on an adaptive coupled random network is proposed. Based on Festinger's idea of "cognitive dissonance", in the proposed model an agent can either make opinion exchange with a neighbor according to the bounded confidence mechanism, or migrate toward another network position in case that the majority of the adjacent agents are beyond the confidence bound. Through numerical simulations, we test how the key factors, such as the interconnectivity of the two communities, the confidence bound or the communal tolerance to diversity, the initial distributions of the opinions, and the level of sense of community, affect the final opinion state of the system. The overall analyses show a general picture of the dynamics of opinions on an adaptive network with community structure. In particular, the results reveal that the clustering of similar agents has a bifurcating function for the opinion dynamics. Given that the inter-communal influence is high, the clustering fosters the global consensus. If the inter-communal influence is weak, the clustering would instead intensify polarization and thus hinder the formation of global consensus. The factors of the communal tolerances and interconnectivity leverage the bifurcating effect.

scholarly journals DYNAMICS OF DISCRETE OPINIONS WITHOUT COMPROMISE

2013 ◽  
Vol 16 (06) ◽  
pp. 1350010 ◽  
Author(s):  
M. KAAN ÖZTÜRK
Keyword(s):  
Extreme Value Distribution ◽  
Opinion Dynamics ◽  
Homogeneous System ◽  
Generalized Extreme Value Distribution ◽  
Agent Based ◽  
Pairwise Interactions ◽  
Bounded Confidence ◽  
Maximum Tolerance ◽  
Gambler’S Ruin ◽  
Gambler's Ruin Problem

A new agent-based, bounded-confidence model for discrete one-dimensional opinion dynamics is presented. The agents interact if their opinions do not differ by more than a tolerance parameter. In pairwise interactions, one of the pair, randomly selected, converts to the opinion of the other. The model can be used to simulate cases where no compromise is possible, such as choices of substitute goods, or other exclusive choices. The homogeneous case with maximum tolerance is equivalent to the Gambler's Ruin problem. A homogeneous system always ends up in an absorbing state, which can have one or more surviving opinions. An upper bound for the final number of opinions is given. The distribution of absorption times fits the generalized extreme value distribution. The diffusion coefficient of an opinion increases linearly with the number of opinions within the tolerance parameter. A general master equation and specific Markov matrices are given. The software code developed for this study is provided as a supplement.

scholarly journals Practical consensus in bounded confidence opinion dynamics

Automatica ◽  
2021 ◽  
Vol 129 ◽  
pp. 109683
Author(s):  
Francesco Vasca ◽  
Carmela Bernardo ◽  
Raffaele Iervolino
Keyword(s):  
Opinion Dynamics ◽  
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 Modeling Confirmation Bias and Peer Pressure in Opinion Dynamics

2021 ◽  
Vol 9 ◽  
Author(s):  
Longzhao Liu ◽  
Xin Wang ◽  
Xuyang Chen ◽  
Shaoting Tang ◽  
Zhiming Zheng
Keyword(s):  
Public Opinion ◽  
Large Scale ◽  
Confirmation Bias ◽  
Opinion Dynamics ◽  
Peer Pressure ◽  
Homogeneous Population ◽  
Agent Based ◽  
Collective Decisions ◽  
Personal Opinion ◽  
The Impact

Confirmation bias and peer pressure are regarded as the main psychology origins of personal opinion adjustment. Each show substantial impacts on the formation of collective decisions. Nevertheless, few attempts have been made to study how the interplay between these two mechanisms affects public opinion evolution on large-scale social networks. In this paper, we propose an agent-based model of opinion dynamics which incorporates the conjugate effect of confirmation bias (characterized by the population identity scope and initiative adaptation speed) and peer pressure (described by a susceptibility threshold and passive adaptation speed). First, a counterintuitive non-monotonous phenomenon arises in the homogeneous population: the number of opinion clusters first increases and then decreases to one as the population identity scope becomes larger. We then consider heterogeneous populations where “impressionable” individuals with large susceptibility to peer pressure and “confident” individuals with small susceptibility coexist. We find that even a small fraction of impressionable individuals could help eliminate public polarization when population identity scope is relatively large. In particular, the impact of impressionable agents would be greater if these agents are hubs. More intriguingly, while impressionable individuals have randomly distributed initial opinions, most of them would finally evolve to moderates. We highlight the emergence of these “impressionable moderates” who are easily influenced, yet are important in public opinion competition, which may inspire efficient strategies in winning competitive campaigns.

Agents and Social Interaction Insights from Social Psychology

2010 ◽  
pp. 74-91
Author(s):  
Joseph C. Bullington
Keyword(s):  
Social Psychology ◽  
Social Interaction ◽  
Social Perception ◽  
Attribution Theory ◽  
Interpersonal Relations ◽  
Human Interaction ◽  
Artificial Agents ◽  
Agent Based ◽  
Human Agent ◽  
Agent Interaction

Social interaction represents a powerful new locus of research in the quest to build more truly humanlike artificial agents. The work in this area, as in the field of human computer interaction, generally, is becoming more interdisciplinary in nature. In this spirit, the present chapter will survey concepts and theory from social psychology, a field many researchers may be unfamiliar with. Dennett’s notion of the intentional system will provide some initial grounding for the notion of social interaction, along with a brief discussion of conversational agents. The body of the chapter will then survey the areas of animal behavior and social psychology most relevant to human-agent interaction, concentrating on the areas of interpersonal relations and social perception. Within the area of social perception, the focus will be on the topics of emotion and attribution theory. Where relevant, research in the area of agent-human interaction will be discussed. The chapter will conclude with a brief survey of the use of agent-based modeling and simulation in social theory. The future looks very promising for researchers in this area; the complex problems involved in developing artificial agents who have mind-like attributes will require an interdisciplinary effort.

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