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dc.contributor.authorHein, Oliver
dc.contributor.authorSchwind, Michael
dc.contributor.authorKönig, Wolfgang
dc.date2006-08-01
dc.date.accessioned2018-01-16T08:54:41Z
dc.date.available2018-01-16T08:54:41Z
dc.date.issued2006
dc.identifier.issn1861-8936
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/12566
dc.description.abstractThe study of network topologies provides interesting insights into the way in which the principles on which interconnected systems are constructed influence the dynamics of diffusion and communication processes in many kinds of socio-technical systems. Empirical research has shown that there are principles of construction similar to those of the laws of nature for social networks and their technical derivatives, like E-mail networks, the internet, publication co-authoring, or business collaboration. For decades, the paradigm of a randomly connected network has been used as a model for real world networks, in ignorance of the fact that they are only a poor fit for such networks. Apparently, all the above-mentioned networks share the same building blocks. They attach new members over time and the attachment prefers existing members that are already well connected. This principle of “preferential attachment” leads to interesting properties that have to be taken into consideration when analyzing and designing systems with some kind of network background.What are called “scale-free” networks seems to be a better fit for the description of real world networks. They use preferential attachment as a construction principle to resample real world networks. Their behavior in terms of diffusion and communication processes is fundamentally different from that of random networks.To illustrate the potential value of the discovery of scale-free networks for applications in information systems related research, an example will be used in this article to illustrate their usefulness for realistic network modeling. A scale-free communication network of security traders will show what impact network topology has on the dynamics of complex socio-technical systems.
dc.publisherSpringer
dc.relation.ispartofWirtschaftsinformatik: Vol. 48, No. 4
dc.relation.ispartofseriesWIRTSCHAFTSINFORMATIK
dc.subjectCommunication Networks
dc.subjectDiffusion
dc.subjectRandom Networks
dc.subjectScale-Free Networks
dc.subjectSocio-Technical Networks
dc.titleScale-free networks
dc.typeText/Journal Article
mci.reference.pages267-275
gi.identifier.doi10.1007/s11576-006-0058-2


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