Life, Death and Preferential Attachment

Abstract

Scientific communities are characterized by strong stratification. The highly skewed frequency distribution of citations of published scientific papers suggests a relatively small number of active, cited papers embedded in a sea of inactive and uncited papers. We propose an analytically soluble model which allows for the death of nodes. This model provides an excellent description of the citation distributions for live and dead papers in the SPIRES database. Further, this model suggests a novel and general mechanism for the generation of power law distributions in networks whenever the fraction of active nodes is small.

5 pages, 2 figures

References in corpus (7)

• Emergence of scaling in random networks
• Statistical mechanics of complex networks
• The structure and function of complex networks
• Evolution of networks
• Connectivity of Growing Random Networks
• Organization of Growing Random Networks
• Citation Networks in High Energy Physics

Cited by in corpus (15)

• The first-mover advantage in scientific publication
• Log-Networks
• Temporal effects in the growth of networks
• A quantitative analysis of measures of quality in science
• Modelling Aging Characteristics in Citation Networks
• Fractional Dynamics of Network Growth Constrained by aging Node Interactions
• Loss of sustainability in scientific work
• Modeling the average shortest path length in growth of word-adjacency networks
• Power-law citation distributions are not scale-free
• Live and Dead Nodes
• Asymmetric access to information impacts the power-law exponent in networks
• Activity ageing in growing networks
• A short-ranged memory model with preferential growth
• Stratified economic exchange on networks
• Hot-Get-Richer Network Growth Model