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tfg_laura_guerra_aragones.pdf (614.74 KB)

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Bachelor thesis

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2021-06-20

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cc-by-nc-nd (c) Laura Guerra Aragonés, 2021
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/185121

Anàlisi de xarxes socials mitjançant cadenes de Markov

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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.

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Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2021, Director: María Isabel García Planas i M. Eulàlia Montoro López

Subject

Processos de Markov, Treballs de fi de grau, Matrius (Matemàtica), Àlgebra lineal, Xarxes socials en línia

Subject (English)

Markov processes, Bachelor's theses, Matrices, Linear algebra, Online social networks

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Treballs Finals de Grau (TFG) - Matemàtiques

Citation

GUERRA ARAGONÉS, Laura. Anàlisi de xarxes socials mitjançant cadenes de Markov. [consulted: 12 of August of 2026]. Available at: https://hdl.handle.net/2445/185121

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