Scale-free networks.

By Albert-László Barabási, Eric Bonabeau. Scientific American, 2003

654 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/69075373d47d7f7287e73262514c54129659575f

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Citations in the corpus

Towards a Theory of Scale-Free Graphs: Definition, Properties, and Implications (2005, background): “Of particular interest here is that a study of SF models of the Internet’s router topology is reported to show that “the removal of just a few key hubs from the Internet splintered the system into tiny groups of hopelessly isolated routers” [16].”
Agent-based simulation of innovation diffusion: a review (2011, background): “More specifically, many (but not all) social networks exhibit the scale-free-ness property, i.e., the probability P ( k ) that a node in the network is connected to k other nodes decays as a power law (Barabási and Bonabeau 2003).”
Research, part of a Special Feature on Resilience Through Multi-scalar Collaboration Surmountable Chasms: Networks and Social Innovation for Resilient Systems (2011, background): “…(Milgram 1967, Watts 2003); and “scale-free” networks, which are defined by power law degree distributions and have a few actors or hubs that are highly connected to other actors, while most are connected to only a few others (Yamagishi et al. 1988, Barabási and Bonabeau 2003, Schnettler 2009).”
Thinking inside the box? Intellectual structure of the knowledge base of innovation research (1988–2008) (2013, background): “These included Nunnally (1978), Mumford and Gustafson (1988), Altman (1995), Frable (1997), Weick and Quinn (1999), Bargh and McKenna (2004), and Latham and Pinder (2005).”
Modeling The Diffusion Of Residential Photovoltaic Systems In Italy: An Agent-based Simulation (2013, background): “SWNs are based on the idea that every individual is connected to anyone else through no more than six degrees of separation (Barabási and Bonabeau, 2003).”
Beyond Gaussian averages: redirecting international business and management research toward extreme events and power laws (2007, background): “Studying the World Wide Web, Barabási et al. (2000) find that the structure of the Web shows a power law distribution, where most nodes have only a few”