"The use of {\it dyadic interaction} between agents, in combination with {\it homophily} (the pri... more "The use of {\it dyadic interaction} between agents, in combination with {\it homophily} (the principle that
``likes attract'') in the Axelrod model for the study of cultural dissemination has two important problems: the
prediction of monoculture in large societies and an extremely narrow window of noise levels in which diversity with
local convergence is obtained. Recently, the inclusion of {\it social influence} has proven to overcome them (A. Flache
and M. W. Macey, arXiv:0808.2710). Here we extend the Axelrod model with social influence interaction for the study of
Mass Media effects through the inclusion of a super-agent which acts over the whole system and has nonnull overlap with
each agent of the society. The dependence with different parameters as the initial social diversity, size effects, Mass
Media strength and noise is outlined. Our results might be relevant in several socio-economic contexts and for the
study of the emergence of collective behavior in complex social systems."
Coupled biological and chemical systems, neural networks, social interacting species, the Interne... more Coupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web, are only a few examples of systems composed by a large number of highly interconnected dynamical units. The first approach to capture the global properties of such systems is to model them as graphs whose nodes represent the dynamical units, and whose links stand for the interactions between them. On the one hand, scientists have to cope with structural issues, such as characterizing the topology of a complex wiring architecture, revealing the unifying principles that are at the basis of real networks, and developing models to mimic the growth of a network and reproduce its structural properties. On the other hand, many relevant questions arise when studying complex networks’ dynamics, such as learning how a large ensemble of dynamical systems that interact through a complex wiring topology can behave collectively. We review the major concepts and results recently achieved in the study of the structure and dynamics of complex networks, and summarize the relevant applications of these ideas in many different disciplines, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
"The use of {\it dyadic interaction} between agents, in combination with {\it homophily} (the pri... more "The use of {\it dyadic interaction} between agents, in combination with {\it homophily} (the principle that
``likes attract'') in the Axelrod model for the study of cultural dissemination has two important problems: the
prediction of monoculture in large societies and an extremely narrow window of noise levels in which diversity with
local convergence is obtained. Recently, the inclusion of {\it social influence} has proven to overcome them (A. Flache
and M. W. Macey, arXiv:0808.2710). Here we extend the Axelrod model with social influence interaction for the study of
Mass Media effects through the inclusion of a super-agent which acts over the whole system and has nonnull overlap with
each agent of the society. The dependence with different parameters as the initial social diversity, size effects, Mass
Media strength and noise is outlined. Our results might be relevant in several socio-economic contexts and for the
study of the emergence of collective behavior in complex social systems."
Coupled biological and chemical systems, neural networks, social interacting species, the Interne... more Coupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web, are only a few examples of systems composed by a large number of highly interconnected dynamical units. The first approach to capture the global properties of such systems is to model them as graphs whose nodes represent the dynamical units, and whose links stand for the interactions between them. On the one hand, scientists have to cope with structural issues, such as characterizing the topology of a complex wiring architecture, revealing the unifying principles that are at the basis of real networks, and developing models to mimic the growth of a network and reproduce its structural properties. On the other hand, many relevant questions arise when studying complex networks’ dynamics, such as learning how a large ensemble of dynamical systems that interact through a complex wiring topology can behave collectively. We review the major concepts and results recently achieved in the study of the structure and dynamics of complex networks, and summarize the relevant applications of these ideas in many different disciplines, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
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Papers by yamir moreno
``likes attract'') in the Axelrod model for the study of cultural dissemination has two important problems: the
prediction of monoculture in large societies and an extremely narrow window of noise levels in which diversity with
local convergence is obtained. Recently, the inclusion of {\it social influence} has proven to overcome them (A. Flache
and M. W. Macey, arXiv:0808.2710). Here we extend the Axelrod model with social influence interaction for the study of
Mass Media effects through the inclusion of a super-agent which acts over the whole system and has nonnull overlap with
each agent of the society. The dependence with different parameters as the initial social diversity, size effects, Mass
Media strength and noise is outlined. Our results might be relevant in several socio-economic contexts and for the
study of the emergence of collective behavior in complex social systems."
``likes attract'') in the Axelrod model for the study of cultural dissemination has two important problems: the
prediction of monoculture in large societies and an extremely narrow window of noise levels in which diversity with
local convergence is obtained. Recently, the inclusion of {\it social influence} has proven to overcome them (A. Flache
and M. W. Macey, arXiv:0808.2710). Here we extend the Axelrod model with social influence interaction for the study of
Mass Media effects through the inclusion of a super-agent which acts over the whole system and has nonnull overlap with
each agent of the society. The dependence with different parameters as the initial social diversity, size effects, Mass
Media strength and noise is outlined. Our results might be relevant in several socio-economic contexts and for the
study of the emergence of collective behavior in complex social systems."