Mixing beliefs among interacting agents

2000 ◽  
Vol 03 (01n04) ◽  
pp. 87-98 ◽  
Author(s):  
Guillaume Deffuant ◽  
David Neau ◽  
Frederic Amblard ◽  
Gérard Weisbuch
Keyword(s):  
Opinion Dynamics ◽  
Interacting Agents ◽  
Continuous Opinions

We present a model of opinion dynamics in which agents adjust continuous opinions as a result of random binary encounters whenever their difference in opinion is below a given threshold. High thresholds yield convergence of opinions towards an average opinion, whereas low thresholds result in several opinion clusters: members of the same cluster share the same opinion but are no longer influenced by members of other clusters.

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.

scholarly journals Voter and Majority Dynamics with Biased and Stubborn Agents

2020 ◽  
Vol 181 (4) ◽  
pp. 1239-1265
Author(s):  
Arpan Mukhopadhyay ◽  
Ravi R. Mazumdar ◽  
Rahul Roy
Keyword(s):  
Majority Rule ◽  
Branching Processes ◽  
Mean Field ◽  
Opinion Dynamics ◽  
Majority Opinion ◽  
Rule Model ◽  
Interacting Agents ◽  
The Mean ◽  
Fully Connected ◽  
Mean Time

Abstract We study binary opinion dynamics in a fully connected network of interacting agents. The agents are assumed to interact according to one of the following rules: (1) Voter rule: An updating agent simply copies the opinion of another randomly sampled agent; (2) Majority rule: An updating agent samples multiple agents and adopts the majority opinion in the selected group. We focus on the scenario where the agents are biased towards one of the opinions called the preferred opinion. Using suitably constructed branching processes, we show that under both rules the mean time to reach consensus is $$\varTheta (\log N)$$ Θ ( log N ) , where N is the number of agents in the network. Furthermore, under the majority rule model, we show that consensus can be achieved on the preferred opinion with high probability even if it is initially the opinion of the minority. We also study the majority rule model when stubborn agents with fixed opinions are present. We find that the stationary distribution of opinions in the network in the large system limit using mean field techniques.

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.

scholarly journals THE IMPORTANCE OF DISAGREEING: CONTRARIANS AND EXTREMISM IN THE CODA MODEL

2010 ◽  
Vol 13 (05) ◽  
pp. 621-634 ◽  
Author(s):  
ANDRÉ C. R. MARTINS ◽  
CLEBER D. KUBA
Keyword(s):  
Opinion Dynamics ◽  
Original Model ◽  
Binary Choice ◽  
Exchange Information ◽  
Continuous Opinions

In this paper, we study the effects of introducing contrarians in a model of Opinion Dynamics where the agents have internal continuous opinions, but exchange information only about a binary choice that is a function of their continuous opinion, the CODA model. We observe that the hung election scenario that arises when contrarians are introduced in discrete opinion models still happens. However, it is weaker and it should not be expected in every election. Finally, we also show that the introduction of contrarians make the tendency towards extremism of the original model weaker, indicating that the existence of agents that prefer to disagree might be an important aspect and help society to diminish extremist opinions.

scholarly journals Nonparametric inference of interaction laws in systems of agents from trajectory data

2019 ◽  
Vol 116 (29) ◽  
pp. 14424-14433 ◽  
Author(s):  
Fei Lu ◽  
Ming Zhong ◽  
Sui Tang ◽  
Mauro Maggioni
Keyword(s):  
Opinion Dynamics ◽  
Analytical Form ◽  
Trajectory Data ◽  
Cell Dynamics ◽  
Fundamental Physics ◽  
Heterogeneous Agent ◽  
Agent Based ◽  
Interacting Agents ◽  
The Social ◽  
Nonparametric Statistical

Inferring the laws of interaction in agent-based systems from observational data is a fundamental challenge in a wide variety of disciplines. We propose a nonparametric statistical learning approach for distance-based interactions, with no reference or assumption on their analytical form, given data consisting of sampled trajectories of interacting agents. We demonstrate the effectiveness of our estimators both by providing theoretical guarantees that avoid the curse of dimensionality and by testing them on a variety of prototypical systems used in various disciplines. These systems include homogeneous and heterogeneous agent systems, ranging from particle systems in fundamental physics to agent-based systems that model opinion dynamics under the social influence, prey–predator dynamics, flocking and swarming, and phototaxis in cell dynamics.

scholarly journals VECTOR OPINION DYNAMICS IN A BOUNDED CONFIDENCE CONSENSUS MODEL

2005 ◽  
Vol 16 (10) ◽  
pp. 1535-1551 ◽  
Author(s):  
SANTO FORTUNATO ◽  
VITO LATORA ◽  
ALESSANDRO PLUCHINO ◽  
ANDREA RAPISARDA
Keyword(s):  
General Pattern ◽  
Opinion Dynamics ◽  
Square Lattice ◽  
Consensus Model ◽  
One Dimensional ◽  
Interacting Agents ◽  
Bounded Confidence ◽  
Uniform Probability Distribution ◽  
Different Shapes ◽  
The Continuum

We study the continuum opinion dynamics of the compromise model of Krause and Hegselmann for a community of mutually interacting agents by solving numerically a rate equation. The opinions are here represented by two-dimensional vectors with real-valued components. We study the situation starting from a uniform probability distribution for the opinion configuration and for different shapes of the confidence range. In all cases, we find that the thresholds for consensus and cluster merging either coincide with their one-dimensional counterparts, or are very close to them. The symmetry of the final opinion configuration, when more clusters survive, is determined by the shape of the opinion space. If the latter is a square, which is the case we consider, the clusters in general occupy the sites of a square lattice, although we sometimes observe interesting deviations from this general pattern, especially near the center of the opinion space.

COMPARING EFFECTS OF CLUSTER-COUPLED PATTERNS ON OPINION DYNAMICS

2012 ◽  
Vol 23 (07) ◽  
pp. 1250050 ◽  
Author(s):  
YUN LIU ◽  
XIA-MENG SI ◽  
YAN-CHAO ZHANG
Keyword(s):  
Community Structure ◽  
Social Cohesion ◽  
Small World ◽  
Opinion Dynamics ◽  
Scale Free ◽  
Update Rules ◽  
Opinion Evolution ◽  
Multiple Cluster ◽  
Better Than ◽  
Continuous Opinions

Community structure is another important feature besides small-world and scale-free property of complex networks. Communities can be coupled through specific fixed links between nodes, or occasional encounter behavior. We introduce a model for opinion evolution with multiple cluster-coupled patterns, in which the interconnectivity denotes the coupled degree of communities by fixed links, and encounter frequency controls the coupled degree of communities by encounter behaviors. Considering the complicated cognitive system of people, the CODA (continuous opinions and discrete actions) update rules are used to mimic how people update their decisions after interacting with someone. It is shown that, large interconnectivity and encounter frequency both can promote consensus, reduce competition between communities and propagate some opinion successfully across the whole population. Encounter frequency is better than interconnectivity at facilitating the consensus of decisions. When the degree of social cohesion is same, small interconnectivity has better effects on lessening the competence between communities than small encounter frequency does, while large encounter frequency can make the greater degree of agreement across the whole populations than large interconnectivity can.

scholarly journals ABOUT THE POWER TO ENFORCE AND PREVENT CONSENSUS BY MANIPULATING COMMUNICATION RULES

2007 ◽  
Vol 10 (02) ◽  
pp. 251-269 ◽  
Author(s):  
JAN LORENZ ◽  
DIEMO URBIG
Keyword(s):  
Mathematical Analysis ◽  
Opinion Dynamics ◽  
The Other ◽  
Entire Group ◽  
Communication Plan ◽  
Other Hand ◽  
Individual Strategies ◽  
Large Groups ◽  
Continuous Opinions

We explore the possibilities of enforcing and preventing consensus in continuous opinion dynamics that result from modifications in the communication rules. We refer to the model of Weisbuch and Deffuant, where n agents adjust their continuous opinions as a result of random pairwise encounters whenever their opinions differ not more than a given bound of confidence ε. A high ε leads to consensus, while a lower ε leads to a fragmentation into several opinion clusters. We drop the random encounter assumption and ask: How small may ε be such that consensus is still possible with a certain communication plan for the entire group? Mathematical analysis shows that ε may be significantly smaller than in the random pairwise case. On the other hand, we ask: How large may ε be such that preventing consensus is still possible? In answering this question, we prove Fortunato's simulation result that consensus cannot be prevented for ε > 0.5 for large groups. Next, we consider opinion dynamics under different individual strategies and examine their power to increase the chances of consensus. One result is that balancing agents increase chances of consensus, especially if the agents are cautious in adapting their opinions. However, curious agents increase chances of consensus only if those agents are not cautious in adapting their opinions.

scholarly journals CONTINUOUS OPINIONS AND DISCRETE ACTIONS IN OPINION DYNAMICS PROBLEMS

2008 ◽  
Vol 19 (04) ◽  
pp. 617-624 ◽  
Author(s):  
ANDRÉ C. R. MARTINS
Keyword(s):  
Opinion Dynamics ◽  
Updating Rule ◽  
Dynamics Problems ◽  
Continuous Opinions

A model where agents show discrete behavior regarding their actions, but have continuous opinions that are updated by interacting with other agents is presented. This new updating rule is applied to both the voter and Sznajd models for interaction between neighbors, and its consequences are discussed. The appearance of extremists is naturally observed and it seems to be a characteristic of this model.

Sign in / Sign up

Export Citation Format

Share Document