The validation of (advanced) bibliometric indicators through peer assessments: A comparative study using data from InCites and F1000

TL;DR

This study evaluates the validity of various bibliometric indicators by comparing them with peer ratings from F1000, finding that Percentile in Subject Area correlates most strongly with expert assessments.

Contribution

It provides a comparative validation of multiple bibliometric metrics against peer evaluations using a comprehensive biomedical dataset.

Findings

Percentile in Subject Area has the highest correlation with peer ratings.

Several citation-based metrics show at least medium correlation with peer assessments.

Normalized indicators like Category Actual/Expected Citations are validated as effective measures.

Abstract

The data of F1000 provide us with the unique opportunity to investigate the relationship between peers' ratings and bibliometric metrics on a broad and comprehensive data set with high-quality ratings. F1000 is a post-publication peer review system of the biomedical literature. The comparison of metrics with peer evaluation has been widely acknowledged as a way of validating metrics. Based on the seven indicators offered by InCites, we analyzed the validity of raw citation counts (Times Cited, 2nd Generation Citations, and 2nd Generation Citations per Citing Document), normalized indicators (Journal Actual/Expected Citations, Category Actual/Expected Citations, and Percentile in Subject Area), and a journal based indicator (Journal Impact Factor). The data set consists of 125 papers published in 2008 and belonging to the subject category cell biology or immunology. As the results show, Percentile in Subject Area achieves the highest correlation with F1000 ratings; we can assert that for further three other indicators (Times Cited, 2nd Generation Citations, and Category Actual/Expected Citations) the 'true' correlation with the ratings reaches at least a medium effect size.