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DTSTART;VALUE=DATE:20231103T153000
DTEND;VALUE=DATE:20231103T153000
UID:14633@agenda.unifr.ch
DESCRIPTION:In recent years, the models and methodologies typically adopted in physics \nhave proven useful for studying various social phenomena. In this thesis, we \nborrow concepts from physics to explore different models of highly complex \nsocial systems. In constructing these models, we aim to capture general insights \nthrough statistical mechanics and probability theory while keeping them simple \nand intuitive. The ultimate goal is not to fully understand the examined social \nphenomena, a challenging or even impossible task, but rather to provide a \nstarting point and inspiration for future research. \nWe begin this thesis with a brief introduction to social physics in Chapter 1. \nSpecifically, we introduce the basic concepts of complex systems, such as \nsocial systems. We then provide a historical overview of the emergence of \nsociophysics and discuss, through subjective considerations, the potential, \nlimitations, and future objectives that physicists approaching social sciences \nshould strive for. In the following two chapters, we study different models of \nsocial interaction: dyadic interaction and interaction within groups. In \nparticular, in Chapter 2, we examine the pairwise matching problem from a \ndifferent perspective. While traditional matching theory considers rational \nagents with complete information, we study a more realistic version where \nindividuals have only local information and self-organize to achieve a final \nmatching that demonstrates properties different from classical matching \nproblem solutions. Using a similar methodology, we propose a simple \nnegotiation model between two individuals. In Chapter 3, we address the \nproblem of community and group formation. First, we show analytically \ninteresting properties of the clustering coefficient in social networks with a \nsimple yet non-trivial model. We then introduce a group formation model to \nstudy how different mechanisms for selecting new members influence the \ncohesion and stability of the group. In Chapter 4, instead, we dive into the \ntopical problem of opinion formation. We investigate the mechanisms through \nwhich individuals, independently of social influence, decide to believe certain \nsources of information over others, considering their limited computational \ncapabilities. Finally, in Chapter 5, we provide a broader view of this thesis and social physics in general.
SUMMARY: Statistical physics models of social dynamics
CATEGORIES:Soutenance de mémoire/thèse
LOCATION:PER 08\, 2.73\, Chemin du Musée 3\, 1700 Fribourg
URL;VALUE=URI:https://agenda.unifr.ch/e/fr/14633
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