Agent-Based Models for Opinion Formation: A Bibliographic Survey

Mastroeni, Loretta; Vellucci, Pierluigi; Naldi, Maurizio

doi:10.1109/access.2019.2913787

Cited by 53 publications

(27 citation statements)

References 148 publications

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“…Using the convergence results (18) and the estimate (19), one can show that the limits of the three terms in (21) are zero as k → ∞, that is,ρ indeed satisfies the weak formulation (20). It remains to showρ(x, 0) = ρ 0 (x).…”

Section: Well-posedness Of Dynamicsmentioning

confidence: 95%

“…The problem of disclosing mechanisms preventing consensus and maintaining enduring disagreement between individuals [11] is nowadays referred to as the community cleavage problem or Abelson's diversity puzzle [12], [13]. The interdisciplinary area of sociodynamical modeling [13]- [20] has attracted enormous attention of the research community and is primarily concerned with mechanisms of opinion formation under social influence.…”

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confidence: 99%

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Macroscopic Noisy Bounded Confidence Models With Distributed Radical Opinions

Kolarijani

Proskurnikov

Esfahani

2021

IEEE Trans. Automat. Contr.

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In this article, we study the nonlinear Fokker-Planck (FP) equation that arises as a mean-field (macroscopic) approximation of bounded confidence opinion dynamics, where opinions are influenced by environmental noises and opinions of radicals (stubborn individuals). The distribution of radical opinions serves as an infinite-dimensional exogenous input to the FP equation, visibly influencing the steady opinion profile. We establish mathematical properties of the FP equation. In particular, we (i) show the well-posedness of the dynamic equation, (ii) provide existence result accompanied by a quantitative global estimate for the corresponding stationary solution, and (iii) establish an explicit lower bound on the noise level that guarantees exponential convergence of the dynamics to stationary state. Combining the results in (ii) and (iii) readily yields the input-output stability of the system for sufficiently large noises. Next, using Fourier analysis, the structure of opinion clusters under the uniform initial distribution is examined. The results of analysis are validated through several numerical simulations of the continuum-agent model (partial differential equation) and the corresponding discrete-agent model (interacting stochastic differential equations) for a particular distribution of radicals.Index Terms-Opinion dynamics, distributed parameter systems, stochastic systems, nonlinear systems, stability of NL systems. I. INTRODUCTIONR ECENT decades have witnessed enormous progress in study of complex systems and their system-theoretic properties [1], [2]. The main effort has been invested into the study of "self-organization" and "spontaneous order" phenomena [3] that have inspired the development of synchronization and consensus theory [4], [5]. Paradoxically, these regular behaviors arising from local interactions between subsystems (agents, nodes) of a complex system are studied much better than various "irregular" dynamic effects such as persistent disagreement and clustering, exhibited by many real-world systems. Although some culprits of this asynchrony and dissent (e.g. symmetries and other special structures in the coupling mechanisms, exogenous forces acting on some nodes, heterogeneous dynamics of nodes, etc.) have been revealed in the literature [6]-[10], only a few mathematical models have been proposed that are sufficiently "rich" to capture the

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Section: Well-posedness Of Dynamicsmentioning

confidence: 95%

mentioning

confidence: 99%

Macroscopic Noisy Bounded Confidence Models With Distributed Radical Opinions

Kolarijani

Proskurnikov

Esfahani

2021

IEEE Trans. Automat. Contr.

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“…With the continuously increasing complexity of such ATM systems, agent based methods (ABMs) provide a suitable tool to model such systems with the desired level of abstraction [19]. ABMs are suitable and can enhance the analysis of problem domains which are geographically distributed, contain subsystems in a dynamic environment and where subsystems are required to interact with the environment [30]- [32] and hence, are very suitable for applications in a complex airport network. Individual components of an dynamic, distributed system communicate with each other through simple rules.…”

Section: B Multi-agent Based Methodsmentioning

confidence: 99%

A Multi-Agent Approach for Reactionary Delay Prediction of Flights

et al. 2019

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Flight schedules are highly sensitive to delays and witness these events on a very frequent basis. In an interconnected and interdependent air transportation system, these delays can magnify and cascade as the flight itineraries progress, causing reactionary delays. The airlines, passengers and airports bear the negative economic implications of such phenomenon. The current research draws motivation from this behavior and develops a multi-agent based method to predict the reactionary delays of flights, given the magnitude of primary delay that the flights witness at the beginning of the itinerary. Every flight is modeled as an agent which functions in a dynamic airport environment, receives information about other agents and updates its own arrival and departure schedule. To evaluate the performance of the method, this paper carries out a case study on the flights in Southeast Asia, which covers eleven countries. The model is tested on a six-month ADS-B dataset that is collected for the calendar year 2016. Through the reactionary delay values predicted by the multi-agent based method, the flights are first classified as delayed or un-delayed in terms of departure. The classification results show an average accuracy of 80.7%, with a delay classification threshold of 15 minutes. Further, a delay multiplier index is evaluated, which is a ratio of the total delays (primary+reactionary delays) and the primary delays for each aircraft. The majority of delay multiplier values range between 1-1.5, which signifies that for except a few outliers, the primary delays do not significantly cascade into reactionary delays for the flights in Southeast Asia. The outliers represent scenarios where primary delays magnify and propagate as reactionary delays over subsequent flight legs. Therefore, the proposed method can assist in better flight scheduling by identifying itineraries which experience higher reactionary delays.INDEX TERMS Air traffic management, agent-based method, ground delay analysis, Southeast Asian airports, reactionary delays.

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“…Without loss of generality, we can assume that the interaction is pairwise because at each step there is just one pair of agents interacting with each other. Then the updating is asynchronous, because not all the agents change their opinion at each time step Mastroeni, Vellucci, and Naldi (2019). For simplicity, we can assume ∆t = 1, considering a proper scaling of time.…”

Section: Numerical Testsmentioning

confidence: 99%

“…The flow of works has been quite steady, with scientific papers having started to appear in significant numbers after 2000, as documented e.g. in the surveys Albi et al (2017); Lorenz (2007); Cercel and Trausan-Matu (2014); Mastroeni, Vellucci, and Naldi (2019).…”

Section: Introductionmentioning

confidence: 99%

Contrarian effect in opinion forming: insights from Greta Thunberg phenomenon

Iacomini¹,

Vellucci²

2021

Preprint

Self Cite

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In recent months the figure of Greta Thunberg and the theme of climate changings quickly became the focus of the debate. This has lead to a polarization effect in opinion forming about the climate subject. Starting from the analysis of this phenomenon, we develop an opinion dynamics model in which several types of contrarians agents are considered. Each agent is supposed to have an opinion on several topics related to each other, thus the opinions being formed on these topics are also mutually dependent. The aim of the paper is to investigate the indirect effects of contrarians agents on the collective opinion about these topics. Several numerical tests are presented in order to highlight the main features of the model.

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Agent-Based Models for Opinion Formation: A Bibliographic Survey

Cited by 53 publications

References 148 publications

Macroscopic Noisy Bounded Confidence Models With Distributed Radical Opinions

Macroscopic Noisy Bounded Confidence Models With Distributed Radical Opinions

A Multi-Agent Approach for Reactionary Delay Prediction of Flights

Contrarian effect in opinion forming: insights from Greta Thunberg phenomenon

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