PageRank beyond the Web

TL;DR

PageRank's mathematical principles extend beyond web pages, enabling diverse applications in network analysis, biology, and physics, by evaluating importance within various types of graphs and networks.

Contribution

This paper demonstrates the general applicability of PageRank mathematics across multiple domains beyond web page ranking.

Findings

PageRank is used in bibliometrics and social network analysis.

It applies to road networks, biology, chemistry, neuroscience, and physics.

The underlying mathematics unites diverse applications.

Abstract

Google's PageRank method was developed to evaluate the importance of web-pages via their link structure. The mathematics of PageRank, however, are entirely general and apply to any graph or network in any domain. Thus, PageRank is now regularly used in bibliometrics, social and information network analysis, and for link prediction and recommendation. It's even used for systems analysis of road networks, as well as biology, chemistry, neuroscience, and physics. We'll see the mathematics and ideas that unite these diverse applications.