Behavioral and Topological Heterogeneities in Network Versions of Schelling's Segregation Model

2024-08-10

arXiv.org

AI Summary

This study investigates how behavioral heterogeneity (individual tolerance thresholds) and topological heterogeneity (network clustering and hub nodes) jointly influence Schelling-type residential segregation. We construct a two-dimensional lattice-based heterogeneous social network featuring both local clustering and global hub structures, and conduct agent-based simulations integrating the Schelling and Xie-Zhou preference models. Our key contributions are threefold: first, we demonstrate that the coexistence of dual heterogeneities significantly reduces aggregate segregation levels; second, we identify a critical threshold for segregation collapse driven by hub node density; third, we uncover a novel spatial differentiation mechanism in tolerance distribution—high-tolerance agents concentrate in dense, hub-rich regions, while low-tolerance agents retreat to sparse, peripheral areas—mirroring urban–rural segregation patterns. These findings advance theoretical understanding of segregation attenuation mechanisms and provide a foundation for designing targeted urban governance strategies and anti-discrimination policies.

Technology Category

• Multiagent Systems: Agent-Based Simulation and Emergent Behavior
• Knowledge Representation and Reasoning: Preferences
• Game Theory and Economic Paradigms: Behavioral Game Theory

Application Category

• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• Web Mining and Content Analysis: Content-based information diffusion
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs

Abstract

Agent-based models of residential segregation have been of persistent interest to various research communities since their origin with James Sakoda and popularization by Thomas Schelling. Frequently, these models have sought to elucidate the extent to which the collective dynamics of individual preferences may cause segregation to emerge. This open question has sustained relevance in U.S. jurisprudence. Previous investigation of heterogeneity of behaviors (preferences) by Xie&Zhou has shown reductions in segregation. Meanwhile, previous investigation of heterogeneity of social network topologies by Gandica, Gargiulo, and Carletti has shown no significant impact to observed segregation levels. In the present study, we examined effects of the concurrent presence of both behavioral and topological heterogeneities in network segregation models. Simulations were conducted using both Schelling's and Xie&Zhou's preference models on 2D lattices with varied levels of densification to create topological heterogeneities (i.e., clusters, hubs). Results show a richer variety of outcomes, including novel differences in resultant segregation levels and hub composition. Notably, with concurrent increased representations of heterogeneous preferences and heterogenous topologies, reduced levels of segregation emerge. Simultaneously, we observe a novel dynamic of segregation between tolerance levels as highly tolerant nodes take residence in dense areas and push intolerant nodes to sparse areas mimicking the urban-rural divide.

Problem

• Examines effects of behavioral and topological heterogeneities on segregation.
• Investigates how diverse preferences and network structures influence segregation levels.
• Explores novel dynamics of segregation in urban-rural divide scenarios.

Innovation

• Combined behavioral and topological heterogeneities in models
• Simulations on 2D lattices with varied densification
• Reduced segregation with increased heterogeneity representations