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Churning, power laws, and inequality in a spatial agent-based model of social networks

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  • Jae Beum Cho

    (Cornell University)

  • Yuri S. Mansury

    (Illinois Institute of Technology)

  • Xinyue Ye

    (Kent State University)

Abstract

Amidst many previous network models lacking a spatial dimension, this paper proposes a dynamic agent-based model of social network formation that explicitly considers space. We find that varying the dynamics of agent interaction causes the emergence of differential degree distributions as well as nonlinear dynamics in social and spatial inequalities. The scale-free property of degree connectivity vanishes when tie formation dominates tie dissolution, with power laws re-emerging when tie dissolution is of equal strength or stronger than tie formation. Furthermore, we find a nonlinear relationship between network density and agent inequality in social resources. In particular, multiple phase transitions occur where the relationship is positive in one phase but negative in another. This suggests that, contrary to intuition, higher connectivity can have an adverse distributional impact by benefiting the already privileged. Critically, we find a tradeoff between agent inequality and spatial inequality where the geographic concentration of social resources accompanies a more equal distribution of connectivity. Finally, the disadvantage of agents with limited spatial reach is exacerbated as network density increases. Our results thus highlight the importance of distinguishing between social and spatial inequality in policymaking.

Suggested Citation

  • Jae Beum Cho & Yuri S. Mansury & Xinyue Ye, 2016. "Churning, power laws, and inequality in a spatial agent-based model of social networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(2), pages 275-307, November.
  • Handle: RePEc:spr:anresc:v:57:y:2016:i:2:d:10.1007_s00168-016-0791-4
    DOI: 10.1007/s00168-016-0791-4
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    Cited by:

    1. Shiro Horiuchi, 2021. "Bridging of different sites by bohemians and tourists: analysis by agent-based simulation," Journal of Computational Social Science, Springer, vol. 4(2), pages 567-584, November.

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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • P11 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - Planning, Coordination, and Reform

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