Modeling and numerical simulations of the influenced Sznajd model

Karan, Farshad Salimi Naneh; Srinivasan, Aravinda Ramakrishnan; Chakraborty, Subhadeep

doi:10.1103/physreve.96.022310

Cited by 14 publications

(8 citation statements)

References 23 publications

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“…Such a structure corresponds to a social network represented by a complete graph where each node is associated with one agent, and links indicate possible interactions between individuals. Networks like this one are frequently used to model relations in small groups or cliques where everybody knows each other [36,47]. In order to mimic interactions in larger societies where the social structure is more complicated, complex networks are embraced, and they form a framework for agent-based models [25,32,48].…”

Section: Model Descriptionmentioning

confidence: 99%

Impact of memory on opinion dynamics

Jędrzejewski

Sznajd-Weron

2018

Physica A: Statistical Mechanics and its Applications

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We investigate an agent-based model of opinion dynamics with two types of social response: conformity and independence. Conformity is introduced to the model analogously as in the Sznajd model or q-voter model, which means that only unanimous group exerts peer pressure on individuals. The novelty, in relation to previous versions of the q-voter model, is memory possessed by each agent and external noise T , which plays the role of social temperature. Each agent has its own memories of past experiences related to the social costs and benefits of being independent or conformist. If an agent was awarded in past more for being independent, it will have a greater tendency to be independent than conformist and vice versa. We will show that depending on the social temperature T the system spontaneously organizes into one of two regimes. Below a certain critical social temperature T c , all agents in the society acquire personal traits (so called person state). Some of them become permanent conformists and others start to behave forever independently. This means that initially homogeneous population becomes heterogeneous, and agents respond differently to social influence. For T > T c , all agents with equal probabilities behave independently or conform to peer pressure (so called situation state). This regime change between person and situation state, which reminds the idea of an annealed vs. quenched disorder, affects also public opinion. Particularly interesting results are obtained for individualistic societies, in which public opinion is non-monotonic function of T , which means that there is an optimal social temperature for which an agreement in the society is the highest.

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Section: Model Descriptionmentioning

confidence: 99%

Impact of memory on opinion dynamics

Jędrzejewski

Sznajd-Weron

2018

Physica A: Statistical Mechanics and its Applications

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“…The researchers studied the controllability of the system both mathematically and with simulations. In another article by the mentioned researchers [22], the controllability of the influenced Sznajd model has been studied in depth. The findings of both studies confirm the findings of the present paper regarding controllability of opinion dynamic in social systems.…”

Section: Discussionmentioning

confidence: 99%

Controllability of a Nonlinear Voter Model

Shiran¹

2018

MJMIE

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Converging and emerging behavior of different phenomena call for a strong tool to describe the behavior of mutli-agent systems. Economics and quantitative sociology are two of the most important areas where these behavioral patterns are observed. In this paper, a brief introduction to statistical physics is provided as a tool to understand and investigate the upper-mentioned phenomena. Some of the available interaction models used in quantitative sociology have been presented to get an idea of how they work. Using one of these models, a discrete nonlinear dynamic system is presented. Main focus of this paper is providing necessary tools and solutions for discrete nonlinear dynamical systems.

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“…Regardless of the type of information, its influence will decline over time [3]. Meanwhile, an individual has the characteristics of forgetting, and we define the acceptance of agent to the discount opinions as formula (6), where α is the attenuation coefficient:…”

Section: S(a I X(t)) Represents the Number Of Agents In The I(a I X...mentioning

confidence: 99%

“…In 2006, Grabowski and Kosiński [2] creatively used random interactions between molecules in physics to simulate the communication process between people, forming the famous Issing model [2]. With the deepening of research, scholars have proposed Voters model [3][4][5], Sznajd model [6][7][8], and so on. Because these models divide the opinions values into independent points, so they are called discrete opinion evolution models.…”

Section: Introductionmentioning

confidence: 99%

Opinion Dynamics Model with Bounded Confidence and the Sleeper Effect

Wei

Jia

Zhu

et al. 2022

Computational Intelligence and Neuroscience

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The evolution of opinions is a complex mechanism. The evolution of individual opinions is not only influenced by own and others but also by psychological effects. Therefore, based on the classical bounded confidence model and the sleeper effect, a new opinion evolution model is proposed in this paper. In this new opinion evolution model, we increase the opinions on every step and take into account the “discount opinions.” Since mental states for human are not easy to measure, we assumed three different initial networks and carried out simulation experiments. To verify the rationality on our model, we compared the effects with and without the sleeper effect, different thresholds, and discounting opinion ratio on opinion aggregation and convergence. Finally, we found the sleeper effect can differently affect the convergence of opinions in different opinion environments.

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Modeling and numerical simulations of the influenced Sznajd model

Cited by 14 publications

References 23 publications

Impact of memory on opinion dynamics

Impact of memory on opinion dynamics

Controllability of a Nonlinear Voter Model

Opinion Dynamics Model with Bounded Confidence and the Sleeper Effect

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