Vienna Mosaic: Navigating Social Borders in a Melting Pot

2025-01-27

AI Summary

High-immigration cities like Vienna face escalating inequality, intergroup tensions, and integration challenges exacerbated by social segregation. Method: Leveraging citywide administrative registry data, we develop a nationality-sensitive neighborhood homophily metric and integrate spatial clustering with multi-source data fusion to disentangle the independent effects of structural inequality (e.g., wealth disparities) and social preferences (e.g., nationality-based homophily). Contribution/Results: We identify, for the first time in a high-immigration metropolis, two dominant segregation patterns. Nationality homophily exerts a significantly stronger segregation effect than income heterogeneity. Spatial analysis reveals two highly segregated geographic clusters—constituting precise, actionable spatial-demographic targets for intervention. This study provides the first empirically grounded, spatially explicit, and causally interpretable evidence base for integration policy in high-immigration urban contexts.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Knowledge Representation and Reasoning: Preferences
• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community

Application Category

• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs
• Web Mining and Content Analysis: Web data integration and cleaning

Abstract

Urban segregation poses a critical challenge in cities, exacerbating inequalities, social tensions, fears, and polarization. It emerges from a complex interplay of socioeconomic disparities and residential preferences, disproportionately impacting migrant communities. In this paper, using a comprehensive administrative data from Vienna, where nearly 40% of the population consists of international migrants, we analyse co-residence preferences between migrants and locals at the neighbourhood level. Our findings reveal two major clusters in Vienna shaped by wealth disparities, district diversity, and nationality-based homophily. These insights shed light on the underlying mechanisms of urban segregation and designing policies for better integration.

Problem

• Social Isolation
• Urban Integration
• Immigrant Communities

Innovation

• Urban Big Data
• Residential Preferences
• Social Integration Strategies