Evolution of citation networks with the hypergraph formalism

TL;DR

This paper introduces a hypergraph-based evolving model for citation networks that incorporates preferential attachment and aging effects, accurately reflecting real citation distributions and providing analytical insights.

Contribution

The study presents a novel hypergraph formalism for modeling citation network evolution, combining preferential attachment and aging, with analytical and simulation validation.

Findings

The model accurately reproduces real citation distribution patterns.

Aging influences are crucial for the citation decay observed.

Analytical results align with empirical data.

Abstract

In this paper, we proposed an evolving model via the hypergraph to illustrate the evolution of the citation network. In the evolving model, we consider the mechanism combined with preferential attachment and the aging influence. Simulation results show that the proposed model can characterize the citation distribution of the real system very well. In addition, we give the analytical result of the citation distribution using the master equation. Detailed analysis showed that the time decay factor should be the origin of the same citation distribution between the proposed model and the empirical result. The proposed model might shed some lights in understanding the underlying laws governing the structure of real citation networks.