Life, Death and Preferential Attachment

TL;DR

This paper introduces an analytically solvable model incorporating node death to explain citation distribution skewness, revealing a new mechanism for power law networks with few active nodes.

Contribution

It presents a novel model that accounts for node death in network growth, accurately describing citation distributions and proposing a general mechanism for power law formation.

Findings

Model fits citation data from SPIRES database

Reveals a mechanism for power law distributions with few active nodes

Provides analytical solutions for citation and node activity dynamics

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.