Aging in Citation Networks

TL;DR

This paper investigates how the age of papers influences citation patterns in networks, revealing a universal distribution of citation intervals with two distinct power-law regimes.

Contribution

It provides an empirical analysis of citation age distribution, identifying a universal power-law behavior across different citation networks.

Findings

Citation interval distribution follows a power-law decay with exponent -0.9 for recent papers.

For older papers, the decay follows a power-law with exponent -2.

A crossover point around 10 units of time separates the two regimes.

Abstract

In many growing networks, the age of the nodes plays an important role in deciding the attachment probability of the incoming nodes. For example, in a citation network, very old papers are seldom cited while recent papers are usually cited with high frequency. We study actual citation networks to find out the distribution $T(t)$ of $t$, the time interval between the published and the cited paper. For different sets of data we find a universal behaviour: $T(t) \sim t^{-0.9}$ for $t \leq t_c$ and $T(t) \sim t^{-2}$ for $t>t_c$ where $t_c \sim O(10)$.