Live and Dead Nodes
Abstract
Description
In this paper, we explore the consequences of a distinction between `live' and `dead' network nodes; `live' nodes are able to acquire new links whereas `dead' nodes are static. We develop an analytically soluble growing network model incorporating this distinction and show that it can provide a quantitative description of the empirical network composed of citations and references (in- and out-links) between papers (nodes) in the SPIRES database of scientific papers in high energy physics. We also demonstrate that the death mechanism alone can result in power law degree distributions for the resulting network.
12 pages, 3 figures. To be published in Computational and Mathematical Organization Theory
12 pages, 3 figures. To be published in Computational and Mathematical Organization Theory