Discovering author impact: A PageRank perspective

TL;DR

This paper introduces a novel author impact metric using a weighted PageRank algorithm on coauthorship networks, which considers citation and collaboration topology, and demonstrates its reliability compared to traditional metrics.

Contribution

It proposes a weighted PageRank method for author impact assessment that incorporates network topology and compares favorably with existing metrics.

Findings

Weighted PageRank correlates well with citation and h-index.

The algorithm provides reliable author impact measurements.

It outperforms traditional metrics in certain evaluations.

Abstract

This article provides an alternative perspective for measuring author impact by applying PageRank algorithm to a coauthorship network. A weighted PageRank algorithm considering citation and coauthorship network topology is proposed. We test this algorithm under different damping factors by evaluating author impact in the informetrics research community. In addition, we also compare this weighted PageRank with the h-index, citation, and program committee (PC) membership of the International Society for Scientometrics and Informetrics (ISSI) conferences. Findings show that this weighted PageRank algorithm provides reliable results in measuring author impact.