Universal fractal scaling of self-organized networks |
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Authors: | Laurienti Paul J Joyce Karen E Telesford Qawi K Burdette Jonathan H Hayasaka Satoru |
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Affiliation: | a Department of Radiology, Wake Forest University Health Sciences, Winston-Salem, NC 27157, USAb Department of Biomedical Engineering, Wake Forest University Health Sciences, Winston-Salem, NC 27157, USAc Department of Biostatistical Sciences, Wake Forest University Health Sciences, Winston-Salem, NC 27157, USA |
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Abstract: | There is an abundance of literature on complex networks describing a variety of relationships among units in social, biological, and technological systems. Such networks, consisting of interconnected nodes, are often self-organized, naturally emerging without any overarching designs on topological structure yet enabling efficient interactions among nodes. Here we show that the number of nodes and the density of connections in such self-organized networks exhibit a power law relationship. We examined the size and connection density of 47 self-organizing networks of various biological, social, and technological origins, and found that the size-density relationship follows a fractal relationship spanning over 6 orders of magnitude. This finding indicates that there is an optimal connection density in self-organized networks following fractal scaling regardless of their sizes. |
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Keywords: | Fractal scaling Self-organized networks Power-law Network science |
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