Analysis of Reference and Citation Copying in Evolving Bibliographic Networks

TL;DR

This paper introduces RefOrCite, a new model for bibliographic networks that incorporates copying of both references and citations, better capturing structural properties like degree distribution, triangles, and paper obsolescence.

Contribution

RefOrCite extends existing models by allowing copying of both references and citations, enabling analytical insights and improved fit to real bibliographic network data.

Findings

RefOrCite accurately models degree distribution and triangle counts.

It explains the obsolescence of older papers.

It matches observed network properties better than previous models.

Abstract

Extensive literature demonstrates how the copying of references (links) can lead to the emergence of various structural properties (e.g., power-law degree distribution and bipartite cores) in bibliographic and other similar directed networks. However, it is also well known that the copying process is incapable of mimicking the number of directed triangles in such networks; neither does it have the power to explain the obsolescence of older papers. In this paper, we propose RefOrCite, a new model that allows for copying of both the references from (i.e., out-neighbors of) as well as the citations to (i.e., in-neighbors of) an existing node. In contrast, the standard copying model (CP) only copies references. While retaining its spirit, RefOrCite differs from the Forest Fire (FF) model in ways that makes RefOrCite amenable to mean-field analysis for degree distribution, triangle count, and densification. Empirically, RefOrCite gives the best overall agreement with observed degree distribution, triangle count, diameter, h-index, and the growth of citations to newer papers.