Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/185121
Title: Anàlisi de xarxes socials mitjançant cadenes de Markov
Author: Guerra Aragonés, Laura
Director/Tutor: García Planas, María Isabel
Montoro López, M. Eulàlia
Keywords: Processos de Markov
Treballs de fi de grau
Matrius (Matemàtica)
Àlgebra lineal
Xarxes socials en línia
Markov processes
Bachelor's theses
Matrices
Linear algebra
Online social networks
Issue Date: 20-Jun-2021
Abstract: [en] Markov chains are a mathematical tool that permits us to predict the short and long term behaviour of systems that can change state at any instant of time and that fulfil Markov’s property, that is, that the future of the system, in from a known present, it is independent of the past. While it will not be known with certainty, the state of the system in the future can make predictions of future behaviours with the Markov Chains. Markov chains can be studied from the point of view of linear and matrix algebra, specifically from the theory of non-negative matrices. This work aims to analyze the theoretical bases of non-negative matrices, on which Markov chains are based, to be used to design a simple mathematical model applied to the analysis of social networks.
Note: Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2021, Director: María Isabel García Planas i M. Eulàlia Montoro López
URI: http://hdl.handle.net/2445/185121
Appears in Collections:Treballs Finals de Grau (TFG) - Matemàtiques

Files in This Item:
File Description SizeFormat 
tfg_laura_guerra_aragones.pdfMemòria614.74 kBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons