Assessing the true role of coauthors in the h-index measure of an author scientific impact

TL;DR

This paper introduces a PCA-based method to better quantify the influence of co-authors on an author's h-index, revealing that co-authors can significantly impact perceived scientific impact.

Contribution

It proposes a novel PCA-based approach to assess co-authors' roles, providing a more accurate measure of individual contributions to scientific impact.

Findings

Co-authors' influence can be underestimated by traditional h-index.

The PCA method effectively estimates co-authors' contribution weights.

Application to real data demonstrates the method's practicality.

Abstract

A method based on the classical principal component analysis leads to demonstrate that the role of co-authors should give a h-index measure to a group leader higher than usually accepted. The method rather easily gives what is usually searched for, i.e. an estimate of the role (or "weight") of co-authors, as the additional value to an author papers' popularity. The construction of the co-authorship popularity H-matrix is exemplified and the role of eigenvalues and the main eigenvector component are discussed. An example illustrates the points and serves as the basis for suggesting a generally practical application of the concept.