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1Roger Brownü "Social structure becomes actually visible in an anthill; the movements and contacts one sees are not random but patterned. We should also be able to see structure in the life of an American community if we had a sufficiently remote vantage point, a point from which persons would appear to be small moving dots. . . . We should see that these dots do not randomly approach one another, that some are usually together, some meet often, some never. . . . If one could get far enough away from it human life would become pure pattern."
2.2l Milgram, Stanley. 1967. “The Small World Problem.” Psychology Today 2:60–67.l 1967 Stanley Milgram (1933-1984) 5 6 1967 5 “ ”
2.2o Nature. 1998 Jun 4;393(6684):440-2.o Collective dynamics of small-world networks. Watts DJ, Strogatz SH. Department of Theoretical and Applied Mechanics, Cornell University, Ithaca, New York 14853, USA. firstname.lastname@example.org Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks rewired to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them small-world networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
2.2o AJS Volume 105, Number 2 (September 1999): 493–527 493o Networks, Dynamics, and the Small-World Phenomenon1Duncan J. WattsSanta Fe InstituteThe small-world phenomenon formalized in this article as the coincidenceof high local clustering and short global separation, is shownto be a general feature of sparse, decentralized networks that areneither completely ordered nor completely random. Networks of thiskind have received little attention, yet they appear to be widespreadin the social and natural sciences, as is indicated here by three distinctexamples. Furthermore, small admixtures of randomness to anotherwise ordered network can have a dramatic impact on its dynamical,as well as structural, properties—a feature illustrated bya simple model of disease transmission.