Machine learning-based prediction of Sznajd model in complex networks

• Grant number: 24/06882-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: June 01, 2024
• End date: March 10, 2025
• Field of knowledge: Physical Sciences and Mathematics - Physics - General Physics
• Principal Investigator: Francisco Aparecido Rodrigues
• Grantee: Vítor Amorim Fróis
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

The study of opinion dynamics is extremely relevant for understanding the emergence of the polarization phenomenon in social networks. This project aims to use machine learning to predict with high accuracy dynamic variables associated with the Sznajd model in complex networks. We will consider modeling through complex networks, Monte Carlo simulations, and regression methods. The project will contribute to a better understanding of the physics of social phenomena.