Characterization and modeling of casual groups in urban systems

• Grant number: 25/03611-8
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: October 27, 2025
• End date: April 26, 2026
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: José Fernando Fontanari
• Grantee: Matheus Stefanini Mariano
• Supervisor: Dieter Pfoser
• Host Institution: Instituto de Física de São Carlos (IFSC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Institution abroad: George Mason University, United States
• Associated to the scholarship: 24/00582-4 - Collective phenomena in animal groupings, BP.MS

Abstract

Collective phenomena are fundamental to the intricate dynamics of biological and social systems, shaping processes ranging from disease diffusion and resource allocation to rumor propagation, crowd behavior, and the emergence of social norms.A useful proxy for assessing collective behavior is group dynamics - an emergent phenomenon observed in human and animal systems, where groups form and dissolve in seemingly random patterns.Group dynamics can be studied using agent-based models, which allow for the exploration of heterogeneous behavioral profiles. However, these models are often difficult to validate due to the lack of high-quality empirical data.In this context, the goal of this project is to empirically characterize group dynamics in urban settings. By doing so, we aim to address one of the main challenges in modeling and studying group dynamics: the absence of empirical benchmarks for testing and validating the theoretical assumptions underlying the agent-based models we propose.To achieve this goal, we will leverage the expertise and resources of the Center for Geospatial Intelligence at George Mason University. The Center provides access to raw mobility data and has extensive experience in data cleaning and processing, enabling the creation of reliable benchmarks that will serve as the foundation for our analysis and validation efforts. These empirical methods will be integrated into the research carried out in Brazil as part of the candidate's master's program, providing the necessary grounding to calibrate and refine the proposed agent-based model of group dynamics. By bridging high-quality data insights with advanced modeling techniques, the project not only strengthens the academic objectives of the Brazilian master's project but also offers valuable frameworks for broader applications, including evidence-based policymaking and real-world interventions in areas such as public health, urban planning, and the study of social processes. (AU)