Modeling citation networks based on vigorousness and dormancy

TL;DR

This paper introduces a citation network model incorporating vigorousness and dormancy stages, capturing the dynamic activity patterns of papers and reproducing realistic degree distributions.

Contribution

A novel citation network model with stage transitions between vigorous and dormant states, aligning well with real-world citation network data.

Findings

Degree distribution shows right-skewed behavior.

Scale-free networks emerge with target selection.

Exponential networks form with random selection.

Abstract

In citation networks, the activity of papers usually decreases with age and dormant papers may be discovered and become fashionable again. To model this phenomenon, a competition mechanism is suggested which incorporates two factors: vigorousness and dormancy. Based on this idea, a citation network model is proposed, in which a node has two discrete stage: vigorous and dormant. Vigorous nodes can be deactivated and dormant nodes may be activated and become vigorous. The evolution of the network couples addition of new nodes and state transitions of old ones. Both analytical calculation and numerical simulation show that the degree distribution of nodes in generated networks displays a good right-skewed behavior. Particularly, scale-free networks are obtained as the deactivated vertex is target selected and exponential networks are realized for the random-selected case. Moreover, the measurement of four real-world citation networks achieves a good agreement with the stochastic model.