Earlier Web Usage Statistics as Predictors of Later Citation Impact

TL;DR

This study investigates whether early Web usage metrics, like download counts, can serve as immediate predictors of an article's future citation impact, using data from arXiv.org.

Contribution

It introduces a method to predict medium-term citation impact based on short-term Web usage data, providing a faster alternative to traditional citation-based impact assessment.

Findings

Web downloads correlate with future citations

Early usage data can predict medium-term impact

Provides a real-time impact assessment approach

Abstract

The use of citation counts to assess the impact of research articles is well established. However, the citation impact of an article can only be measured several years after it has been published. As research articles are increasingly accessed through the Web, the number of times an article is downloaded can be instantly recorded and counted. One would expect the number of times an article is read to be related both to the number of times it is cited and to how old the article is. This paper analyses how short-term Web usage impact predicts medium-term citation impact. The physics e-print archive (arXiv.org) is used to test this.