Effect of initial concentration and spatial heterogeneity of active agent distribution on opinion dynamics

Balankin, Alexander S.; Cruz, M.; Martínez, Alfredo Trejo

doi:10.1016/j.physa.2011.05.034

Cited by 10 publications

(12 citation statements)

References 66 publications

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“…Consequently, the structure of electoral network is very complex. Nonetheless, some features of electoral dynamics can be simulated on networks with relatively simple structures or even square lattices [11][12][13][14][15][16][17][18][19][20]. This enables us to study how the factors, which have been chosen as the important ones for a phenomenon under study, influence the outcome, while avoiding the possible effects of other attributes.…”

Section: Model and Details Of Numerical Simulationsmentioning

confidence: 99%

“…One can also use appropriate functions of different moments of the probability density function, or, in some cases, the ratio of the mean to median of the spatial distribution [16]. The last is the measure of the degree of spatial concentration of the spin distribution among cells.…”

Section: Spatial Distributions Of Competing Opinionsmentioning

confidence: 99%

“…In this regard, the introduction of a neutral state can also have a considerable impact on the spin dynamics [11][12][13][14][15]. Furthermore, heterogeneities in the initial spatial distributions of non-zero spins also affect the system dynamics [16]. In the context of opinion dynamics, spin states can be associated with competing opinions and uncommitted attitudes.…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, the probability to reach a specific consensus in a majority rule model has a nontrivial initial state dependence [19,20]. The effect of spatial heterogeneity of rival opinions on the opinion dynamics has been studied in [16], using the dominant influence rule model with random noise. It was found that the spatial heterogeneity reduces the opinion's competitiveness defined as the probability to win the competition.…”

Section: Introductionmentioning

confidence: 99%

“…It was found that the spatial heterogeneity reduces the opinion's competitiveness defined as the probability to win the competition. However, the use of a log-logistic distribution, random nose, and a new updating rule in the model studied in [16] introduces too many parameters that govern the opinion dynamics.…”

Section: Introductionmentioning

confidence: 99%

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Effect of Heterogeneity in Initial Geographic Distribution on Opinions’ Competitiveness

Balankin

Cruz

Martínez

et al. 2015

Entropy

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Spin dynamics on networks allows us to understand how a global consensus emerges out of individual opinions. Here, we are interested in the effect of heterogeneity in the initial geographic distribution of a competing opinion on the competitiveness of its own opinion. Accordingly, in this work, we studied the effect of spatial heterogeneity on the majority rule dynamics using a three-state spin model, in which one state is neutral. Monte Carlo simulations were performed on square lattices divided into square blocks (cells). Accordingly, one competing opinion was distributed uniformly among cells, whereas the spatial distribution of the rival opinion was varied from the uniform to heterogeneous, with the median-to-mean ratio in the range from 1 to 0. When the size of discussion group is odd, the uncommitted agents disappear completely after = tr T 3.30 ± 0.05 update cycles, and then the system evolves in a two-state regime with complementary spatial distributions of two competing opinions. Even so, the initial heterogeneity in the spatial distribution of one of the competing opinions causes a decrease of this opinion competitiveness. That is, the opinion with initially heterogeneous spatial distribution has less probability to win, than the opinion with the initially uniform spatial distribution, even when the initial concentrations of both opinions are equal. We found that although the time to consensus OPEN ACCESSEntropy 2015, 17 3161 tr C T T >> , the opinion's recession rate is determined during the first 3.3 update cycles. On the other hand, we found that the initial heterogeneity of the opinion spatial distribution assists the formation of quasi-stable regions, in which this opinion is dominant. The results of Monte Carlo simulations are discussed with regard to the electoral competition of political parties.

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Section: Model and Details Of Numerical Simulationsmentioning

confidence: 99%

Section: Spatial Distributions Of Competing Opinionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effect of Heterogeneity in Initial Geographic Distribution on Opinions’ Competitiveness

Balankin

Cruz

Martínez

et al. 2015

Entropy

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Multifractal approach for a biological porous media: Human dentin case

Sánchez‐Chávez,

Flores‐Cano,

Santiago‐Hernández

et al. 2023

Microscopy Res & Technique

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A multifractal characterization to human dentin porosity is made. Micrographs of human dentin samples gotten from scanning electron microscopy (SEM) were studied in order to characterize porosity. We got the generalized dimensions (multifractal moments) for pore space and matrix skeleton on gray scale and binary images for samples of both gender. For the case, we found that superficial porosity is linked to mass fractal dimension in an approximately linear relationship as for binary images. In addition, probability density distribution (PDD) for pore diameters is found a normal PDD type. Other quantities of interest like mean, standard deviation, maximum and minimum pore diameters, voit ratios, and percentage of chemical composition are reported.Research Highlights SEM sample, images and procedure for multifractal analysis are detailed. Micro patterns in grayscale are multifractal and in binary scale are monofractals. Superficial porosity is relate to mass fractal dimension approximately linearly. From the porosity values, voit ratios are determined. Pores diameters obey a normal PDD.

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A Review of Opinion Dynamics

Xie

Song

2016

Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems

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Effect of initial concentration and spatial heterogeneity of active agent distribution on opinion dynamics

Cited by 10 publications

References 66 publications

Effect of Heterogeneity in Initial Geographic Distribution on Opinions’ Competitiveness

Effect of Heterogeneity in Initial Geographic Distribution on Opinions’ Competitiveness

Multifractal approach for a biological porous media: Human dentin case

A Review of Opinion Dynamics

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