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Research Impact Metrics

A guide for those wanting to use research impact metrics for evaluation, analytics, and reviews, e.g., promotion & tenure.

Author Metrics & Profiles

Can Apply To

Authors

Metric Definition

An author-level metric (although it can also be calculated for any aggregation of publications, e.g. journals, institutions, etc.) calculated from the count of citations to an author’s set of publications.

Metric Calculation

In his 2005 paper proposing the h-index, Hirsch describes the measure thusly: “A scientist has index h if h of his or her Np papers have at least h citations each and the other (Np – h) papers have fewer than ≤ h citations each.” For example, an author with an h-index of 6 has at least six journal articles that have each been cited at least six times each.

Data Sources

Citation data used to calculate the h-index can be retrieved from Google Scholar, Scopus, Web of Science, Dimensions or any other citation index that includes author- and article-level citation information.

Appropriate Use Cases

The h-index has been used as evidence of the scholarly influence of an author’s, or group of authors’, body of work. It is best used in conjunction with other metrics, if at all. Use of the h-index for groups occurs infrequently in practice.

Limitations

Many limitations to the h-index have been identified by experts. The h-index varies by discipline due to varying norms of publishing speed and quantity. Since it does not take into account the longevity of a scholar’s career, it benefits more experienced scholars over early-career individuals. The h-index is unable to differentiate between active and inactive scientists, and is biased towards productive researchers in detriment of selective ones. The h-index is also relatively insensitive to highly cited papers. Many have attempted to fix the h-index’s weaknesses with various computational models that, for example, reward highly-cited papers, correct for career length, rank authors’ papers against other papers published in the same year and source, or count just the average citations of the most high-impact “core” of an author’s work. However, none of these improvements upon the h-index have been as widely adopted as the h-index itself.

Inappropriate Use Cases

The h-index should not be used as a sole metric of scholarly impact, nor should it be used as a direct measure of quality. The h-index should not be used to rank authors who are in different disciplines or those at different stages of their careers.

Available Metric Sources

The h-index can be manually calculated, or you can retrieve it from Google Scholar, Scopus, or Web of Science.

Transparency

The formula for calculating the h-index is openly available. See https://en.wikipedia.org/wiki/H-index

Website

n/a

Timeframe

All time
Information in table from the Metrics Toolkit h-index. Attribution to the Metrics Toolkit editorial team, CC BY. In addition, portions of the Toolkit's guide borrow from “Four reasons to stop caring so much about the h-index” by Stacy Konkiel and are reused here under a CC-BY license.

Many variations of the h-index have been created, such as the g-index, the A-index, and the R-index. However, many of these new author metrics do not help with its many limitations. 

However, Publish or Perish is a unique (free) software tool that allows you to pull out variations of the author h-index that help normalize for multi-authorship, years of publication, highly cited publications, all of which can be useful for comparing across fields and career stage. You can also use this free PoP Word template for gathering your metrics, interpreting them, and comparing them to other researchers.

 

  • Researcher Profiles and Identifiers
    This guide will help you with setting up researcher profiles, connecting them together, reducing the need for needless data entry, author disambiguation, and tracking metrics through the various profiles.