CONTINUOUS OPINION DYNAMICS ON AN ADAPTIVE COUPLED RANDOM NETWORK

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.

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

Advances in Complex Systems ◽

10.1142/s0219525915500022 ◽

2015 ◽

Vol 18 (01n02) ◽

pp. 1550002 ◽

Cited By ~ 8

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.

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Investigating Key Factors for Social Network Evolution and Opinion Dynamics in an Agent-Based Simulation

Lecture Notes in Computer Science - Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Human Communication, Organization and Work ◽

10.1007/978-3-030-49907-5_2 ◽

2020 ◽

pp. 20-39

Author(s):

Patrick Halbach ◽

Laura Burbach ◽

Poornima Belavadi ◽

Johannes Nakayama ◽

Nils Plettenberg ◽

...

Keyword(s):

Social Network ◽

Opinion Dynamics ◽

Network Evolution ◽

Key Factors ◽

Agent Based Simulation ◽

Agent Based ◽

Social Network Evolution

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An Adaptive Bounded-Confidence Model of Opinion Dynamics on Networks

10.31235/osf.io/gcxnf ◽

2021 ◽

Author(s):

Unchitta Kan ◽

Michelle Feng ◽

Mason A. Porter

Keyword(s):

Social Networks ◽

Early Time ◽

Opinion Dynamics ◽

Convergence Time ◽

Confidence Bound ◽

Neighboring Node ◽

Popular Approach ◽

Time Dynamics ◽

Bounded Confidence ◽

Bounded Confidence Model

Individuals who interact with each other in social networks often exchange ideas and influence each other's opinions. A popular approach to studying the dynamics of opinion spread on networks is by examining bounded-confidence (BC) models, in which the nodes of a network have continuous-valued states that encode their opinions and are receptive to other opinions if they lie within some confidence bound of their own opinion. We extend the Deffuant--Weisbuch (DW) model, which is a well-known BC model, by studying opinion dynamics that coevolve with network structure. We propose an adaptive variant of the DW model in which the nodes of a network can (1) alter their opinion when they interact with a neighboring node and (2) break a connection with a neighbor based on an opinion tolerance threshold and then form a new connection to a node following the principle of homophily. This opinion tolerance threshold acts as a threshold to determine if the opinions of adjacent nodes are sufficiently different to be viewed as discordant. We find that our adaptive BC model requires a larger confidence bound than the standard DW model for the nodes of a network to achieve a consensus. Interestingly, our model includes regions with `pseudo-consensus' steady states, in which there exist two subclusters within an opinion-consensus group that deviate from each other by a small amount. We conduct extensive numerical simulations of our adaptive BC model and examine the importance of early-time dynamics and nodes with initial moderate opinions for achieving consensus. We also examine the effects of coevolution on the convergence time of the dynamics.

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CONTINUOUS OPINION DYNAMICS UNDER BOUNDED CONFIDENCE: A SURVEY

International Journal of Modern Physics C ◽

10.1142/s0129183107011789 ◽

2007 ◽

Vol 18 (12) ◽

pp. 1819-1838 ◽

Cited By ~ 334

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.

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An Evacuation Model for Passenger Ships That Includes the Influence of Obstacles in Cabins

Mathematical Problems in Engineering ◽

10.1155/2017/5907876 ◽

2017 ◽

Vol 2017 ◽

pp. 1-21 ◽

Cited By ~ 4

Author(s):

Baocheng Ni ◽

Zhen Li ◽

Pei Zhang ◽

Xiang Li

Keyword(s):

Force Model ◽

Social Force ◽

Key Factors ◽

Social Force Model ◽

Interaction Forces ◽

Factors Affecting ◽

Agent Based ◽

Proposed Model ◽

Passenger Ships ◽

Passenger Behavior

Passenger behavior and ship environment are the key factors affecting evacuation efficiency. However, current studies ignore the interior layout of passenger ship cabins and treat the cabins as empty rooms. To investigate the influence of obstacles (e.g., tables and stools) on cabin evacuation, we propose an agent-based social force model for advanced evacuation analysis of passenger ships; this model uses a goal-driven submodel to determine a plan and an extended social force submodel to govern the movement of passengers. The extended social force submodel considers the interaction forces between the passengers, crew, and obstacles and minimises the range of these forces to improve computational efficiency. We drew the following conclusions based on a series of evacuation simulations conducted in this study: (1) the proposed model endows the passenger with the behaviors of bypassing and crossing obstacles, (2) funnel-shaped exits from cabins can improve evacuation efficiency, and (3) as the exit angle increases, the evacuation time also increases. These findings offer ship designers some insight towards increasing the safety of large passenger ships.

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

SIMULATION ◽

10.1177/0037549718800583 ◽

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.

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DYNAMICS OF DISCRETE OPINIONS WITHOUT COMPROMISE

Advances in Complex Systems ◽

10.1142/s0219525913500100 ◽

2013 ◽

Vol 16 (06) ◽

pp. 1350010 ◽

Cited By ~ 2

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.

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GEOSPATIAL MODELLING APPROACH FOR 3D URBAN DENSIFICATION DEVELOPMENTS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b2-349-2016 ◽

2016 ◽

Vol XLI-B2 ◽

pp. 349-352

Author(s):

O. Koziatek ◽

S. Dragićević ◽

S. Li

Keyword(s):

Key Factors ◽

Agent Based ◽

High Rise ◽

Multi Criteria Evaluation ◽

Metro Vancouver ◽

Proposed Model ◽

Spatial Dimensions ◽

Geospatial Modelling ◽

The City ◽

Modelling Approach

With growing populations, economic pressures, and the need for sustainable practices, many urban regions are rapidly densifying developments in the vertical built dimension with mid- and high-rise buildings. The location of these buildings can be projected based on key factors that are attractive to urban planners, developers, and potential buyers. Current research in this area includes various modelling approaches, such as cellular automata and agent-based modelling, but the results are mostly linked to raster grids as the smallest spatial units that operate in two spatial dimensions. Therefore, the objective of this research is to develop a geospatial model that operates on irregular spatial tessellations to model mid- and high-rise buildings in three spatial dimensions (3D). The proposed model is based on the integration of GIS, fuzzy multi-criteria evaluation (MCE), and 3D GIS-based procedural modelling. Part of the City of Surrey, within the Metro Vancouver Region, Canada, has been used to present the simulations of the generated 3D building objects. The proposed 3D modelling approach was developed using ESRI’s CityEngine software and the Computer Generated Architecture (CGA) language.

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