Ranking game on networks: The evolution of hierarchical society

Zhang, Xinjie; Tang, Yong; Xiong, Jason; Wang, Wei Jia; Zhang, Yicheng

doi:10.1016/j.physa.2019.123140

Cited by 5 publications

(3 citation statements)

References 80 publications

(141 reference statements)

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“…Mathematical models dealing with the problem of social stratification have been introduced only recently, mainly by resorting to the dynamics of social networks in which individuals quest for high status in the social hierarchy (Bardoscia et al 2013;Chang 2013;König and Tessone 2011;König et al 2009;Zhang et al 2020). An approach based on statistical mechanics has been introduced in Dimarco and Toscani (2020).…”

Section: Introductionmentioning

confidence: 99%

A multi-agent description of the influence of higher education on social stratification

Dimarco

Toscani

Zanella

2022

J Econ Interact Coord

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We introduce and discuss a system of one-dimensional kinetic equations describing the influence of higher education in the social stratification of a multi-agent society. The system is obtained by coupling a model for knowledge formation with a kinetic description of the social climbing in which the parameters characterizing the elementary interactions leading to the formation of a social elite are assumed to depend on the degree of knowledge/education of the agents. In addition, we discuss the case in which the education level of an individual is function of the position occupied in the social ranking. With this last assumption, we obtain a fully coupled model in which knowledge and social status influence each other. In the last part, we provide several numerical experiments highlighting the role of education in reducing social inequalities and in promoting social mobility.

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Section: Introductionmentioning

confidence: 99%

A multi-agent description of the influence of higher education on social stratification

Dimarco

Toscani

Zanella

2022

J Econ Interact Coord

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“…Mathematical models dealing with the problem of social stratification have been introduced only recently, mainly by resorting to the dynamics of social networks in which individuals quest for high status in the social hierarchy [3,18,42,43,65]. An approach based on statistical mechanics has been introduced in [25].…”

Section: Introductionmentioning

confidence: 99%

A multi-agent description of the influence of higher education on social stratification

Dimarco¹,

Toscani²,

Zanella³

2021

Preprint

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We introduce and discuss a system of one-dimensional kinetic equations describing the influence of higher education in the social stratification of a multi-agent society. The system is obtained by coupling a model for knowledge formation with a kinetic description of the social climbing in which the parameters characterizing the elementary interactions leading to the formation of a social elite are assumed to depend on the degree of knowledge/education of the agents. In addition, we discuss the case in which the education level of an individual is function of the position occupied in the social ranking. With this last assumption we obtain a fully coupled model in which knowledge and social status influence each other. In the last part, we provide several numerical experiments highlighting the role of education in reducing social inequalities and in promoting social mobility.

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“…He further noticed that social mobility in this hierarchical state appears to be higher in the middle classes than in the upper and lower part of the hierarchy. The correctness of Pareto's social analysis has been recently investigated in a number of studies dealing with the modeling of the dynamics of social networks in which individuals quest for high status in the social hierarchy [2,53,54,80]. There, the social status of individuals is usually ranked according to a certain measure strongly related to centrality in the society.…”

Section: Introductionmentioning

confidence: 99%

Social climbing and Amoroso distribution

Dimarco¹,

Toscani²

2020

Preprint

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We introduce a class of one-dimensional linear kinetic equations of Boltzmann and Fokker-Planck type, describing the dynamics of individuals of a multi-agent society questing for high status in the social hierarchy. At the Boltzmann level, the microscopic variation of the status of agents around a universal desired target, is built up introducing as main criterion for the change of status a suitable value function in the spirit of the prospect theory of Kahneman and Twersky. In the asymptotics of grazing interactions, the solution density of the Boltzmann type kinetic equation is shown to converge towards the solution of a Fokker-Planck type equation with variable coefficients of diffusion and drift, characterized by the mathematical properties of the value function. The steady states of the statistical distribution of the social status predicted by the Fokker-Planck equations belong to the class of Amoroso distributions with Pareto tails, which correspond to the emergence of a social elite. The details of the microscopic kinetic interaction allow to clarify the meaning of the various parameters characterizing the resulting equilibrium. Numerical results then show that the steady state of the underlying kinetic equation is close to Amoroso distribution even in an intermediate regime in which interactions are not grazing.

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Ranking game on networks: The evolution of hierarchical society

Cited by 5 publications

References 80 publications

A multi-agent description of the influence of higher education on social stratification

A multi-agent description of the influence of higher education on social stratification

A multi-agent description of the influence of higher education on social stratification

Social climbing and Amoroso distribution

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