Réka Albert
Professor of physics and biology at Penn State, and co-author of the model that explains why large networks are scale-free.
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Their wordsSystems as diverse as genetic networks or the world wide web are best described as networks with complex topology.
↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 2nd of 8 in this piece
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Their wordsA common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution.
↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 4th of 8 in this piece
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Their wordsThis feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites.
↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 6th of 8 in this piece
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Their wordsA model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 8th of 8 in this piece