Análises estatísticas em redes complexas: propriedades topológicas, críticas e dinâmicas
In this thesis, we address two issues of broad conceptual and practical relevance in the study of complex networks. The first is associated with the topological characterization of networks while the second relates to dynamical processes that occur on top of them. Regarding the first line of study,...
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Định dạng: | doctoralThesis |
Ngôn ngữ: | por |
Được phát hành: |
Universidade Federal do Rio Grande do Norte
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Những chủ đề: | |
Truy cập trực tuyến: | https://repositorio.ufrn.br/jspui/handle/123456789/16618 |
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Tóm tắt: | In this thesis, we address two issues of broad conceptual and practical relevance
in the study of complex networks. The first is associated with the topological characterization
of networks while the second relates to dynamical processes that occur on top
of them. Regarding the first line of study, we initially designed a model for networks
growth where preferential attachment includes: (i) connectivity and (ii) homophily (links
between sites with similar characteristics are more likely). From this, we observe that
the competition between these two aspects leads to a heterogeneous pattern of connections
with the topological properties of the network showing quite interesting results. In
particular, we emphasize that there is a region where the characteristics of sites play an
important role not only for the rate at which they get links, but also for the number of
connections which occur between sites with similar and dissimilar characteristics. Finally,
we investigate the spread of epidemics on the network topology developed, whereas its
dissemination follows the rules of the contact process. Using Monte Carlo simulations,
we show that the competition between states (infected/healthy) sites, induces a transition
between an active phase (presence of sick) and an inactive (no sick). In this context, we
estimate the critical point of the transition phase through the cumulant Binder and ratio
between moments of the order parameter. Then, using finite size scaling analysis, we
determine the critical exponents associated with this transition |
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