From Individual to Collective: Three-State Opinion Dynamics on Single and Multilayer Topologies
Visiting speaker
Irene Ferri
PhD candidate, Universitat de Barcelona
Past Talk
Virtual
Wednesday
May 1, 2024
Watch video
12:00 pm
EST
Virtual
177 Huntington Ave.
11th floor
Devon House
58 St Katharine's Way
London E1W 1LP, UK
Online
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With the aim of explaining and understanding social and psychological phenomena, such as the emergence of consensus or the existence of cognitive dissonance, we will introduce a three-state discrete model and its parameters to encode opinion states. As we explore various topologies for the social structure, ranging from complete graphs to modular structures, we will relate the distinct network characteristics to their impact on model outcomes. When we focus on human behavior, we can delve beyond the social network that represents interactions among people, to the inner network formed by the belief systems within each person. During conversations, we potentially have the opportunity to update our inner state to align with our neighbors' opinions. However, the structure of our inner belief system plays a crucial role in this updating process. We will show how individuals with different belief topologies behave, interact, and are capable of altering both each other's and the global system's behavior.
About the speaker
About the speaker
Irene Ferri holds a Bachelor's degree in Physics from the University of Barcelona, where she continued her academic journey by completing a Master's degree in Computational Modeling. Currently, she is finishing her PhD., under the guidance of Dr. Albert Díaz-Guilera. Her research focuses on opinion dynamics and opinion formation, particularly investigating Ising-like models and bounded confidence models to improve the understanding of the dynamics that govern opinion evolution and spreading in social networks. As part of her doctoral studies, she undertook a Ph.D. stay as an AccelNet-MultiNet fellow at the University of Binghamton, under the mentorship of Dr. Hiroki Sayama. Irene actively collaborates with the Heurística Association at the Institute of Complex Systems of the University of Barcelona. This collaboration enables her to conduct experiments to validate her models and gain insights into real-world opinion dynamics.
Irene Ferri holds a Bachelor's degree in Physics from the University of Barcelona, where she continued her academic journey by completing a Master's degree in Computational Modeling. Currently, she is finishing her PhD., under the guidance of Dr. Albert Díaz-Guilera. Her research focuses on opinion dynamics and opinion formation, particularly investigating Ising-like models and bounded confidence models to improve the understanding of the dynamics that govern opinion evolution and spreading in social networks. As part of her doctoral studies, she undertook a Ph.D. stay as an AccelNet-MultiNet fellow at the University of Binghamton, under the mentorship of Dr. Hiroki Sayama. Irene actively collaborates with the Heurística Association at the Institute of Complex Systems of the University of Barcelona. This collaboration enables her to conduct experiments to validate her models and gain insights into real-world opinion dynamics.