As cities grow larger and more complex, understanding how people move, interact, and make decisions has become central to designing effective urban policies. This challenge was at the heart of Esteban Moro’s intervention at the 3rd edition of the Data Research Meetup, held on December 18 and organized by MagIC.

Professor at Northeastern University and Director of the Social Urban Networks Group at the Network Science Institute, Esteban Moro explored how large-scale behavioral data is reshaping the way cities are analyzed, modelled, and governed. Drawing on research developed mainly in the United States, he showed that traditional urban models - largely based on geographical distance and residential location - are increasingly insufficient to explain how cities function.

At the core of his talk was the idea that cities operate as complex networks driven by human behavior. Using data from mobile phones and location-based services, Moro demonstrated that daily activities such as commuting, shopping, or leisure connect people and places far beyond their immediate neighbourhoods. According to his research, behavioral “distance” often plays a more decisive role than physical proximity in shaping urban dynamics.

Rethinking policy through data-driven urban models

Moro highlighted the limitations of traditional “before-and-after” approaches, which often overestimate the impact of interventions by failing to account for broader systemic changes. Through examples from collaborations with city governments, including work with the City of Boston, he illustrated how network-based approaches and causal inference methods enable more robust and realistic assessments of policy outcomes.

The intervention reinforced a broader message of the Data Research Meetup: addressing contemporary urban challenges requires interdisciplinary perspectives that combine data science, network theory, and social understanding. As cities continue to grow and evolve, Esteban Moro concluded, the ability to model human behavior at scale will be essential for developing more effective, resilient, and socially informed urban policies.