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Descripción
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| Over the past years, new technologies and online social networks, have penetrated into world's population at an accelerated pace. Here we analyze data collected from Twitter, to describe the structural and dynamical patterns of the emergent social networks, based on complexity science. In particular, we define a measure of influence on Twitter, called user efficiency. This measure represents the ratio between the emergent spreading process and the activity employed by this user to influence such process. We found that the user efficiency is universal across several Twitter conversations. In fact, we show that these patterns are actually a reflection of the dynamical rules behind the spreading process, strongly determined by the topological features of the underlying network where information spreads and independent of the way users behave. We also proposed a model to estimate the opinions of the majority of users, by knowing the opinion of the highly influential and efficient ones. The model results in an opinion distribution. We propose a polarization index to determine the extent to which such distributions are polarized. We apply this methodology to political conversations and showed that our methodology is able to determine several levels of polarization, depending on the structure of the underlying network. | |
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Internacional
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Si |
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Nombre congreso
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6th Workshop on Complex Networks (CompleNet 2015) [http://2015.complenet.org] |
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Tipo de participación
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970 |
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Lugar del congreso
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New York (USA) |
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Revisores
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Si |
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ISBN o ISSN
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0000-0000 |
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DOI
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Fecha inicio congreso
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25/03/2015 |
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Fecha fin congreso
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27/03/2015 |
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Desde la página
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33 |
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Hasta la página
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33 |
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Título de las actas
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THE 2015 INTERNATIONAL WORKSHOP ON COMPLEX NETWORKS - FINAL PROGRAM [http://2015.complenet.org/CompleNet_2015/Program_files/FinalProgram2015_1.pdf] |