The role of fanatics in consensus formation

2015 ◽  
Vol 26 (03) ◽  
pp. 1550029 ◽  
Author(s):  
Semra Gündüç
Keyword(s):  
Finite Size ◽  
Opinion Dynamics ◽  
Scaling Relations ◽  
Scaling Relation ◽  
Opinion Formation ◽  
Consensus Formation ◽  
Social Actors ◽  
Size Dependent ◽  
Proposed Model ◽  
Formation Behavior

A model of opinion dynamics with two types of agents as social actors are presented, using the Ising thermodynamic model as the dynamics template. The agents are considered as opportunists which live at sites and interact with the neighbors, or fanatics/missionaries which move from site to site randomly in persuasion of converting agents of opposite opinion with the help of opportunists. Here, the moving agents act as an external influence on the opportunists to convert them to the opposite opinion. It is shown by numerical simulations that such dynamics of opinion formation may explain some details of consensus formation even when one of the opinions are held by a minority. Regardless the distribution of the opinion, different size societies exhibit different opinion formation behavior and time scales. In order to understand general behavior, the scaling relations obtained by comparing opinion formation processes observed in societies with varying population and number of randomly moving agents are studied. For the proposed model two types of scaling relations are observed. In fixed size societies, increasing the number of randomly moving agents give a scaling relation for the time scale of the opinion formation process. The second type of scaling relation is due to the size dependent information propagation in finite but large systems, namely finite-size scaling.

Social Space in Simulation Models

2014 ◽  
pp. 200-219
Author(s):  
Davide Nunes ◽  
Luis Antunes
Keyword(s):  
Social Relations ◽  
Social Space ◽  
Opinion Dynamics ◽  
Simulation Models ◽  
Opinion Formation ◽  
Consensus Formation ◽  
Space Design ◽  
Network Topologies ◽  
Multiple Interaction ◽  
Set Up

In real world scenarios, the formation of consensus is a self-organisation process by which actors have to make a joint assessment about a target subject, be it a decision making problem or the formation of a collective opinion. In social simulation, models of opinion dynamics tackle the opinion formation phenomena. These models try to make an assessment, for instance, of the ideal conditions that lead an interacting group of agents to opinion consensus, polarisation or fragmentation. This chapter investigates the role of social relation structure in opinion dynamics and consensus formation. The authors present an agent-based model that defines social relations as multiple concomitant social networks and explore multiple interaction games in this structural set-up. They discuss the influence of complex social network topologies where actors interact in multiple distinct networks. The chapter builds on previous work about social space design with multiple social relations to determine the influence of such complex social structures in a process such as opinion formation.

Consensus formation in continuous opinion dynamics on quasiperiodic lattices

2019 ◽  
Vol 31 (01) ◽  
pp. 2050012
Author(s):  
T. F. A. Alves ◽  
F. W. S. Lima ◽  
A. Macedo-Filho ◽  
G. A. Alves
Keyword(s):  
Kinetic Monte Carlo ◽  
Finite Size ◽  
Opinion Dynamics ◽  
Universality Class ◽  
External Noise ◽  
Continuous Phase ◽  
Formation Model ◽  
Consensus Formation ◽  
Kinetic Monte Carlo Simulations ◽  
Binder Cumulant

We studied the Biswas–Chatterjee–Sen (BCS) consensus formation model, also known as the Kinetic Continuous Opinion Dynamics (KCOD) model on quasiperiodic lattices by using Kinetic Monte Carlo simulations and Finite Size Scaling technique. Our results are consistent with a continuous phase transition, controlled by an external noise. We obtained the order parameter [Formula: see text], defined as the averaged opinion, the fourth-order Binder cumulant [Formula: see text] and susceptibility [Formula: see text] as functions of the noise parameter. We estimated the critical noises for Penrose and Ammann–Beenker lattices. We also considered seven-fold and nine-fold quasiperiodic lattices and estimated the respective critical noises as well. Irrespective of rotational and translational long-range order of the lattice, the system falls in the same universality class of the two-dimensional Ising model. Quasiperiodic order is irrelevant and it does not change any critical exponents for BCS model.

Consensus formation simulation in a social network modeling controversial opinion dynamics with pairwise interactions

2017 ◽  
Vol 28 (05) ◽  
pp. 1750058 ◽  
Author(s):  
María G. Medina-Guevara ◽  
Jorge E. Macías-Díaz ◽  
Armando Gallegos ◽  
Héctor Vargas-Rodríguez
Keyword(s):  
Social Network ◽  
Network Modeling ◽  
Opinion Dynamics ◽  
Opinion Formation ◽  
Consensus Formation ◽  
Pairwise Interactions ◽  
Finite Difference Equations ◽  
The Social ◽  
Social Network Modeling ◽  
Strong Consensus

In this work, we consider a system of coupled finite-difference equations which incorporates a variety of opinion formation models, and use it to describe the dynamics of opinions on controversial subjects. The social network consists of a finite number of agents with pairwise interactions at discrete times. Meanwhile, the opinion of each agent is updated following a general nonlinear law which considers parameters identified as the personal constants of each of the members. We establish conditions that guarantee the existence of global attracting points (strong consensus) and intervals (weak consensus). Moreover, we note that these conditions are independent of the weight matrix and the number of agents of the network. Two particular scenarios are investigated numerically in order to confirm the validity of the analytical results.

CONSENSUS FORMATION IN WEIGHTED SCALE-FREE NETWORKS

2009 ◽  
Vol 20 (05) ◽  
pp. 677-686 ◽  
Author(s):  
KE HU ◽  
YI TANG
Keyword(s):  
Opinion Dynamics ◽  
Opinion Formation ◽  
Consensus Formation ◽  
Scale Free ◽  
Weighted Networks ◽  
Global Consensus ◽  
Dynamical Behaviors ◽  
Scale Free Networks ◽  
Unweighted Network ◽  
Large Heterogeneity

We develop a consensus model for studying opinion dynamics in weighted networks and investigate the effects of both the distribution of weights and the correlations between weight and degree on dynamical behaviors of opinion formation. Our results suggest that a global consensus in the weighted networks to reach is more difficult than that in unweighted network, and strongly depends on the heterogeneity of connection strengths. In addition, in the weighted network with very large heterogeneity of connection strengths, only single macroscopic opinion cluster can be formed, which differs from the behavior in the unweighted network where the next-largest macroscopic opinion cluster may exist.

scholarly journals Opinion dynamics with backfire effect and biased assimilation

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256922
Author(s):  
Xi Chen ◽  
Panayiotis Tsaparas ◽  
Jefrey Lijffijt ◽  
Tijl De Bie
Keyword(s):  
Opinion Dynamics ◽  
Formation Model ◽  
Opinion Formation ◽  
Social Phenomena ◽  
Proposed Model ◽  
The Social ◽  
Unrestricted Access ◽  
Biased Assimilation ◽  
Backfire Effect ◽  
Novel Model

The democratization of AI tools for content generation, combined with unrestricted access to mass media for all (e.g. through microblogging and social media), makes it increasingly hard for people to distinguish fact from fiction. This raises the question of how individual opinions evolve in such a networked environment without grounding in a known reality. The dominant approach to studying this problem uses simple models from the social sciences on how individuals change their opinions when exposed to their social neighborhood, and applies them on large social networks. We propose a novel model that incorporates two known social phenomena: (i) Biased Assimilation: the tendency of individuals to adopt other opinions if they are similar to their own; (ii) Backfire Effect: the fact that an opposite opinion may further entrench people in their stances, making their opinions more extreme instead of moderating them. To the best of our knowledge, this is the first DeGroot-type opinion formation model that captures the Backfire Effect. A thorough theoretical and empirical analysis of the proposed model reveals intuitive conditions for polarization and consensus to exist, as well as the properties of the resulting opinions.

Opinion Dynamics Optimization by Varying Susceptibility to Persuasion via Non-Convex Local Search

2021 ◽  
Vol 16 (2) ◽  
pp. 1-34
Author(s):  
Rediet Abebe ◽  
T.-H. HUBERT Chan ◽  
Jon Kleinberg ◽  
Zhibin Liang ◽  
David Parkes ◽  
...  
Keyword(s):  
Local Search ◽  
Objective Function ◽  
Iterative Process ◽  
Large Scale ◽  
Opinion Dynamics ◽  
Theoretical Models ◽  
Global Optimum ◽  
Local Optimum ◽  
Opinion Formation ◽  
Long Line

A long line of work in social psychology has studied variations in people’s susceptibility to persuasion—the extent to which they are willing to modify their opinions on a topic. This body of literature suggests an interesting perspective on theoretical models of opinion formation by interacting parties in a network: in addition to considering interventions that directly modify people’s intrinsic opinions, it is also natural to consider interventions that modify people’s susceptibility to persuasion. In this work, motivated by this fact, we propose an influence optimization problem. Specifically, we adopt a popular model for social opinion dynamics, where each agent has some fixed innate opinion, and a resistance that measures the importance it places on its innate opinion; agents influence one another’s opinions through an iterative process. Under certain conditions, this iterative process converges to some equilibrium opinion vector. For the unbudgeted variant of the problem, the goal is to modify the resistance of any number of agents (within some given range) such that the sum of the equilibrium opinions is minimized; for the budgeted variant, in addition the algorithm is given upfront a restriction on the number of agents whose resistance may be modified. We prove that the objective function is in general non-convex. Hence, formulating the problem as a convex program as in an early version of this work (Abebe et al., KDD’18) might have potential correctness issues. We instead analyze the structure of the objective function, and show that any local optimum is also a global optimum, which is somehow surprising as the objective function might not be convex. Furthermore, we combine the iterative process and the local search paradigm to design very efficient algorithms that can solve the unbudgeted variant of the problem optimally on large-scale graphs containing millions of nodes. Finally, we propose and evaluate experimentally a family of heuristics for the budgeted variant of the problem.

scholarly journals Nonlocal and Size-Dependent Dielectric Function for Plasmonic Nanoparticles

2019 ◽  
Vol 9 (15) ◽  
pp. 3083
Author(s):  
Kai-Jian Huang ◽  
Shui-Jie Qin ◽  
Zheng-Ping Zhang ◽  
Zhao Ding ◽  
Zhong-Chen Bai
Keyword(s):  
Metallic Nanoparticles ◽  
High Efficiency ◽  
Finite Size ◽  
Plasmonic Nanostructures ◽  
Accurate Analysis ◽  
Finite Size Effects ◽  
Size Dependent ◽  
Quantum Size ◽  
The Impact ◽  
Electron Energy Loss

We develop a theoretical approach to investigate the impact that nonlocal and finite-size effects have on the dielectric response of plasmonic nanostructures. Through simulations, comprehensive comparisons of the electron energy loss spectroscopy (EELS) and the optical performance are discussed for a gold spherical dimer system in terms of different dielectric models. Our study offers a paradigm of high efficiency compatible dielectric theoretical framework for accounting the metallic nanoparticles behavior combining local, nonlocal and size-dependent effects in broader energy and size ranges. The results of accurate analysis and simulation for these effects unveil the weight and the evolution of both surface and bulk plasmons vibrational mechanisms, which are important for further understanding the electrodynamics properties of structures at the nanoscale. Particularly, our method can be extended to other plasmonic nanostructures where quantum-size or strongly interacting effects are likely to play an important role.

Size-dependent properties of transition metal clusters: from molecules to crystals and surfaces – computational studies with the program ParaGauss

2015 ◽  
Vol 17 (43) ◽  
pp. 28463-28483 ◽  
Author(s):  
Thomas M. Soini ◽  
Notker Rösch
Keyword(s):  
Transition Metal ◽  
Metal Clusters ◽  
Scaling Relations ◽  
Computational Studies ◽  
Transition Metal Clusters ◽  
Size Dependent ◽  
Adsorption Complexes

Scaling relations on the basis of accurate DFT results are a useful tool for analyzing size-dependent properties of transition metal clusters and adsorption complexes on such systems.

PHYSICS OF THE MIND: OPINION DYNAMICS AND DECISION MAKING PROCESSES BASED ON A BINARY NETWORK MODEL

2008 ◽  
Vol 22 (25n26) ◽  
pp. 4482-4494 ◽  
Author(s):  
F. V. KUSMARTSEV ◽  
KARL E. KÜRTEN
Keyword(s):  
Decision Making ◽  
Social Networks ◽  
Chaotic Behavior ◽  
Opinion Dynamics ◽  
Human Mind ◽  
Critical Parameters ◽  
Opinion Formation ◽  
Natural Catastrophes ◽  
Risk Condition ◽  
Binary Network

We propose a new theory of the human mind. The formation of human mind is considered as a collective process of the mutual interaction of people via exchange of opinions and formation of collective decisions. We investigate the associated dynamical processes of the decision making when people are put in different conditions including risk situations in natural catastrophes when the decision must be made very fast or at national elections. We also investigate conditions at which the fast formation of opinion is arising as a result of open discussions or public vote. Under a risk condition the system is very close to chaos and therefore the opinion formation is related to the order disorder transition. We study dramatic changes which may happen with societies which in physical terms may be considered as phase transitions from ordered to chaotic behavior. Our results are applicable to changes which are arising in various social networks as well as in opinion formation arising as a result of open discussions. One focus of this study is the determination of critical parameters, which influence a formation of stable mind, public opinion and where the society is placed “at the edge of chaos”. We show that social networks have both, the necessary stability and the potential for evolutionary improvements or self-destruction. We also show that the time needed for a discussion to take a proper decision depends crucially on the nature of the interactions between the entities as well as on the topology of the social networks.

USE OF STRAIN GRADIENT THEORY FOR MODELING THE SIZE-DEPENDENT PULL-IN OF ROTATIONAL NANO-MIRROR IN THE PRESENCE OF MOLECULAR FORCE

2013 ◽  
Vol 27 (18) ◽  
pp. 1350083 ◽  
Author(s):  
Y. TADI BENI ◽  
M. ABADYAN
Keyword(s):  
Strain Gradient ◽  
Continuum Theory ◽  
Strain Gradient Theory ◽  
Gradient Theory ◽  
Cross Sectional ◽  
Size Dependent ◽  
Proposed Model ◽  
Molecular Force ◽  
Intrinsic Material Length ◽  
Material Length

Experiments reveal that mechanical behavior of nanostructures is size-dependent. Herein, the size dependent pull-in instability of torsional nano-mirror is investigated using strain gradient nonclassic continuum theory. The governing equation of the mirror is derived taking the effect of electrostatic Coulomb and molecular van der Waals (vdW) forces into account. Variation of the rotation angle of the mirror as a function of the applied voltage is obtained and the instability parameters i.e., pull-in voltage and pull-in angle are determined. Nano-mirrors with square and circular cross-sectional beams are investigated as case studies. It is found that when the thickness of the torsional nano-beam is comparable with the intrinsic material length scales, size effect can substantially increase the instability parameters of the rotational mirror. Moreover, the effect of vdW forces on the size-dependent pull-in instability of the system is discussed. The proposed model is able to predict the experimental results more accurately than the previous classic models and reduce the gap between experiment and previous theories.

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