Efficient Algorithms for Citation Network Analysis

TL;DR

This paper introduces efficient, linear-time algorithms for analyzing citation networks, focusing on computing specific arc weights and identifying important subnetworks, with applications to scientific literature and patents.

Contribution

It presents novel linear algorithms for arc weight computation and a method to identify key subnetworks based on these weights in citation networks.

Findings

Algorithms are linear in the number of arcs.

Theoretical properties of arc weights are established.

Practical applications demonstrated on citation networks of SOM literature and US patents.

Abstract

In the paper very efficient, linear in number of arcs, algorithms for determining Hummon and Doreian's arc weights SPLC and SPNP in citation network are proposed, and some theoretical properties of these weights are presented. The nonacyclicity problem in citation networks is discussed. An approach to identify on the basis of arc weights an important small subnetwork is proposed and illustrated on the citation networks of SOM (self organizing maps) literature and US patents.