CEU Electronic Theses and Dissertations, 2025
| Author | Napoli, Ludovico |
|---|---|
| Title | Socioeconomic patterns in human mobility and social networks |
| Summary | Socioeconomic status (SES) has a profound influence on human life, shaping health outcomes, social mobility, and access to resources. Beyond these well-recognized effects, SES also impacts how people navigate physical spaces and build social connections, contributing to patterns of segregation and social cohesion. Recent advancements in large-scale digital data offer an opportunity to explore these interactions in unprecedented detail. This thesis uses a mix of digital, traditional, and innovative data sources to analyze the connections between SES, mobility, and social networks, aiming to uncover how SES-driven behaviors shape segregation patterns in response to external shocks and create disparities within universal mobility models. Chapter 1 provides a comprehensive foundation, reviewing key theories, methodologies, and models that frame the interactions between SES, physical movement, and social networks. Drawing from social science, network theory, data science, and mobility research, it sets the stage for the data-focused analyses that follow. Chapter 2 establishes the methodology for observing SES patterns in large-scale mobility and social network data, addressing the challenge of capturing detailed, representative SES and behavioral data. By aligning digital traces with socioeconomic maps, this chapter creates a statistically representative sample of individuals, connecting SES attributes with precise, granular proxies of movement and social connections. This framework enables the detailed exploration of SES-driven behaviors across diverse populations. Exploring how the COVID-19 pandemic influenced social and spatial interactions, Chapter 3 uses Call Detail Records (CDRs) from Sierra Leone to analyze changes in socioeconomic segregation during lockdown. While mobility segregation increased as expected under movement restrictions, social segregation decreased, with individuals maintaining broader social ties to offset reduced physical contact. These findings reveal how SES influences adaptation to external shocks and variations in social resilience. Chapter 4 investigates individual deviations from universal human mobility models, focusing on the Exploration and Preferential Return (EPR) model. Through analysis of large-scale GPS data, it reveals that the model’s accuracy varies across different populations, with significant biases emerging among specific sociodemographic groups. In sum, this thesis contributes to understanding SES’s role in mobility and social networks, providing insights for policies that promote inclusion, resilience, and equitable access to resources. |
| Supervisor | Karsai Márton |
| Department | Network Science PhD |
| Full text | https://www.etd.ceu.edu/2025/napoli_ludovico.pdf |
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