title: Properties of a random attachment growing network.
abstract: In this study we introduce and analyze the statistical structural properties of a model of growing networks which may be relevant to social networks. At each step a new node is added which selects k possible partners from the existing network and joins them with probability delta by undirected edges. The "activity" of the node ends here; it will get new partners only if it is selected by a newcomer. The model produces an infinite-order phase transition when a giant component appears at a specific value of delta, which depends on k. The average component size is discontinuous at the transition. In contrast, the network behaves significantly different for k=1. There is no giant component formed for any delta and thus in this sense there is no phase transition. However, the average component size diverges for delta> or =1/2.
authors.affiliation: Department of Biophysics, KFKI Research Institute for Particle and Nuclear Physics of the Hungarian Academy of Sciences, Budapest, Hungary.
authors.forename: László
authors.initials: L
authors.lastname: Zalányi
authors.forename: Gábor
authors.initials: G
authors.lastname: Csárdi
authors.forename: Tamás
authors.initials: T
authors.lastname: Kiss
authors.forename: Máté
authors.initials: M
authors.lastname: Lengyel
authors.forename: Rebecca
authors.initials: R
authors.lastname: Warner
authors.forename: Jan
authors.initials: J
authors.lastname: Tobochnik
authors.forename: Péter
authors.initials: P
authors.lastname: Erdi
mesh_terms: D016000:Cluster Analysis; D019058:Community Networks; D016571:Neural Networks, Computer; D011157:Population Dynamics; D011897:Random Allocation; D012944:Social Support