scholarly journals An agent-based model of multi-dimensional opinion dynamics and opinion alignment

2020 ◽  
Author(s):  
Simon Schweighofer ◽  
David Garcia ◽  
Frank Schweitzer
Keyword(s):  
Resistance To Change ◽  
Dimensional Space ◽  
Opinion Dynamics ◽  
Emergent Properties ◽  
Agent Based Model ◽  
Agent Based ◽  
Ideological Dimension ◽  
The Individual ◽  
Dissonance Theory ◽  
Proximity Voting

It is known that individual opinions on different policy issues often align to a dominant ideological dimension (e.g. ``left'' vs. ``right'') and become increasingly polarized. We provide an agent-based model that reproduces these two stylized facts as emergent properties of an opinion dynamics in a multi-dimensional space of continuous opinions. The mechanisms for the change of agents' opinions in this multi-dimensional space are derived from cognitive dissonance theory and structural balance theory. We test assumptions from proximity voting and from directional voting regarding their ability to reproduce the expected emerging properties. We further study how the emotional involvement of agents, i.e. their individual resistance to change opinions, impacts the dynamics. We identify two regimes for the global and the individual alignment of opinions. If the affective involvement is high and shows a large variance across agents, this fosters the emergence of a dominant ideological dimension. Agents align their opinions along this dimension in opposite directions, i.e. create a state of polarization.

scholarly journals Opinion Expression Dynamics in Social Media Chat Groups: An Integrated Quasi-Experimental and Agent-Based Model Approach

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Siyuan Ma ◽  
Hongzhong Zhang
Keyword(s):  
Social Media ◽  
Peer Support ◽  
Online Communication ◽  
Opinion Dynamics ◽  
Agent Based Model ◽  
Agent Based ◽  
Individual Level ◽  
Opinion Expression ◽  
Quasi Experimental ◽  
The Individual

Social media chat groups, such as WeChat and WhatsApp groups, are widely applied in online communication. This research has conducted two studies to examine the individual level and collective level’s opinion dynamics in those groups. The opinion dynamic is driven by two variables, people’s perceived peer support and willingness of opinion expression. The perceived peer support influences the willingness of opinion expression, and the willingness influences the dynamics of real opinion-expression. First, the quasi-experimental study recruited twenty-five participants as the observation group and found that decreasing perceived peer support would significantly increase individuals’ expression willingness to protect his/her opinion. To generalize the individual level findings to a collective level, the second study treated the social media chat groups as an undirected fully-connected social network and simulated people’s opinion expression dynamics with an agent-based model. The simulation indicated that (1) with the help of increased willingness of opinion expression, the minority opinion supporters as a collective did not fall silent but continue to express themselves and (2) increasing willingness of opinion expression would maintain the existence of minority opinion but could not help the minority reverse to the majority.

scholarly journals Agent based models to investigate cooperation between cancer cells

2015 ◽  
Author(s):  
Joao Xavier ◽  
William Chang
Keyword(s):  
Growth Factor ◽  
Cancer Cells ◽  
Solid Tumor ◽  
Kin Selection ◽  
Evolution Of Cooperation ◽  
Emergent Properties ◽  
Agent Based Model ◽  
Agent Based ◽  
Chemical Gradients ◽  
Close Proximity

We present a type of agent-based model that uses off-lattice spheres to represent individual cells in a solid tumor. The model calculates chemical gradients and determines the dynamics of the tumor as emergent properties of the interactions between the cells. As an example, we present an investigation of cooperation among cancer cells where cooperators secrete a growth factor that is costly to synthesize. Simulations reveal that cooperation is favored when cancer cells from the same lineage stay in close proximity. The result supports the hypothesis that kin selection, a theory that explains the evolution of cooperation in animals, also applies to cancers.

MACRO- AND MICROPRUDENTIAL POLICIES: SWEET AND LOWDOWN IN A CREDIT NETWORK AGENT-BASED MODEL

2019 ◽  
pp. 1-20
Author(s):  
Ermanno Catullo ◽  
Federico Giri ◽  
Mauro Gallegati
Keyword(s):  
Systemic Risk ◽  
Financial Stability ◽  
Agent Based Model ◽  
Agent Based ◽  
Macroprudential Policies ◽  
The Stability ◽  
The Individual ◽  
The Cost ◽  
Individual Choices ◽  
Credit Network

The paper presents an agent-based model reproducing a stylized credit network that evolves endogenously through the individual choices of firms and banks. We introduce in this framework a financial stability authority in order to test the effects of different prudential policy measures designed to improve the resilience of the economic system. Simulations show that a combination of micro- and macroprudential policies reduces systemic risk but at the cost of increasing banks’ capital volatility. Moreover, the agent-based methodology allows us to implement an alternative meso regulatory framework that takes into consideration the connections between firms and banks. This policy targets only the more connected banks, increasing their capital requirement in order to reduce the diffusion of local shocks. Our results support the idea that the mesoprudential policy is able to reduce systemic risk without affecting the stability of banks’ capital structure.

ANALYZING THE AGENT-BASED MODEL AND ITS IMPLICATIONS

2003 ◽  
Vol 06 (03) ◽  
pp. 331-347 ◽  
Author(s):  
YUTAKA I. LEON SUEMATSU ◽  
KEIKI TAKADAMA ◽  
NORBERTO E. NAWA ◽  
KATSUNORI SHIMOHARA ◽  
OSAMU KATAI
Keyword(s):  
Social Sciences ◽  
Internal Structure ◽  
Design Methodology ◽  
Social Systems ◽  
Agent Based Model ◽  
Social Phenomena ◽  
Agent Based ◽  
Individual Level ◽  
The Social ◽  
The Individual

Agent-based models (ABMs) have been attracting the attention of researchers in the social sciences, becoming a prominent paradigm in the study of complex social systems. Although a great number of models have been proposed for studying a variety of social phenomena, no general agent design methodology is available. Moreover, it is difficult to validate the accuracy of these models. For this reason, we believe that some guidelines for ABMs design must be devised; therefore, this paper is a first attempt to analyze the levels of ABMs, identify and classify several aspects that should be considered when designing ABMs. Through our analysis, the following implications have been found: (1) there are two levels in designing ABMs: the individual level, related to the design of the agents' internal structure, and the collective level, which concerns the design of the agent society or macro-dynamics of the model; and (2) the mechanisms of these levels strongly affect the outcomes of the models.

scholarly journals Identifying Synergistic Interventions to Address COVID-19 Using a Large Scale Agent-Based Model

2020 ◽  
Author(s):  
Junjiang Li ◽  
Philippe J. Giabbanelli
Keyword(s):  
Public Health ◽  
Large Scale ◽  
Contact Tracing ◽  
Remote Work ◽  
Agent Based Model ◽  
Agent Based ◽  
Global Pandemic ◽  
Small Set ◽  
Factorial Design Of Experiments ◽  
The Individual

AbstractThere is a range of public health tools and interventions to address the global pandemic of COVID-19. Although it is essential for public health efforts to comprehensively identify which interventions have the largest impact on preventing new cases, most of the modeling studies that support such decision-making efforts have only considered a very small set of interventions. In addition, previous studies predominantly considered interventions as independent or examined a single scenario in which every possible intervention was applied. Reality has been more nuanced, as a subset of all possible interventions may be in effect for a given time period, in a given place. In this paper, we use cloud-based simulations and a previously published Agent-Based Model of COVID-19 (Covasim) to measure the individual and interacting contribution of interventions on reducing new infections in the US over 6 months. Simulated interventions include face masks, working remotely, stay-at-home orders, testing, contact tracing, and quarantining. Through a factorial design of experiments, we find that mask wearing together with transitioning to remote work/schooling has the largest impact. Having sufficient capacity to immediately and effectively perform contact tracing has a smaller contribution, primarily via interacting effects.

scholarly journals Memory-Based Reduced Modelling and Data-Based Estimation of Opinion Spreading

2021 ◽  
Vol 31 (1) ◽  
Author(s):  
Niklas Wulkow ◽  
Péter Koltai ◽  
Christof Schütte
Keyword(s):  
Interaction Network ◽  
Opinion Dynamics ◽  
Agent Based ◽  
Agent Interaction ◽  
Network Topologies ◽  
Projection Formalism ◽  
Nonlinear Autoregressive Model ◽  
The Individual ◽  
Nonlinear Autoregressive ◽  
With Memory

AbstractWe investigate opinion dynamics based on an agent-based model and are interested in predicting the evolution of the percentages of the entire agent population that share an opinion. Since these opinion percentages can be seen as an aggregated observation of the full system state, the individual opinions of each agent, we view this in the framework of the Mori–Zwanzig projection formalism. More specifically, we show how to estimate a nonlinear autoregressive model (NAR) with memory from data given by a time series of opinion percentages, and discuss its prediction capacities for various specific topologies of the agent interaction network. We demonstrate that the inclusion of memory terms significantly improves the prediction quality on examples with different network topologies.

scholarly journals Testing the impact of direct and indirect flood warnings on population behaviour using an agent-based model

2020 ◽  
Vol 20 (8) ◽  
pp. 2281-2305
Author(s):  
Thomas O'Shea ◽  
Paul Bates ◽  
Jeffrey Neal
Keyword(s):  
Hydrodynamic Model ◽  
Emergent Properties ◽  
Incident Management ◽  
Daily Routine ◽  
Agent Based Model ◽  
Hazard Management ◽  
Agent Based ◽  
Flood Dynamics ◽  
The Impact ◽  
Bass Diffusion Model

Abstract. This paper uses a coupled hydrodynamic agent-based model (HABM) to investigate the effect of direct or indirect warnings in flood incident response. This model uses the LISFLOOD-FP hydrodynamic model and the NetLogo agent-based framework and is applied to the 2005 flood event in Carlisle, UK. The hydrodynamic model provides a realistic simulation of detailed flood dynamics through the event, whilst the agent-based model component enables simulation and analysis of the complex, in-event social response. NetLogo enables alternative probabilistic daily routine and agent choice scenarios for the individuals of Carlisle to be simulated in a coupled fashion with the flood inundation. Specifically, experiments are conducted using a novel “enhanced social modelling component” based on the Bass diffusion model. From the analysis of these simulations, management stress points (predictable or otherwise) can be presented to those responsible for hazard management and post-event recovery. The results within this paper suggest that these stress points can be present, or amplified, due to a lack of preparedness or a lack of phased evacuation measures. Furthermore, the methods outlined here have the potential for application elsewhere to reduce the complexity and improve the effectiveness of flood incident management. The paper demonstrates the influence that emergent properties have on systematic vulnerability and risk from natural hazards in coupled socio-environmental systems.

scholarly journals Multi-Equilibria Regulation Agent-Based Model of Opinion Dynamics in Social Networks

2013 ◽  
Vol 11 (1) ◽  
pp. 51-70 ◽  
Author(s):  
Andreas Koulouris ◽  
Ioannis Katerelos ◽  
Theodore Tsekeris
Keyword(s):  
Social Networks ◽  
Opinion Dynamics ◽  
Agent Based Model ◽  
Agent Based
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