Knowledge Guides: Publishing Your Research: Author-level Metrics

Author-level Metrics

Author-level metrics are citation metrics that measure the bibliometric impact of individual authors. H-index is the best-known author-level metric. Since it was proposed by JE Hirsch in 2005 it has gained a lot of popularity amongst researchers while bibliometics scholars proposed a few variants to account for its weaknesses (g-index, m-index are good examples).

Demystifying Scholarly Metrics: A Practical Guide
ISBN: 9798216073147
Both librarians and professors can be overwhelmed by the bewildering number of scholarly metrics. This user-friendly book demystifies them, helping librarians become familiar with scholarly metrics and giving them the confidence to assist faculty at their institutions. It also equips faculty authors with the knowledge to evaluate journals and use metrics to track their scholarly impact. Several controversies exist in the scholarly metrics landscape, including a disagreement between the proponents of altmetrics and traditional bibliometrics. Even more contentious debates are breaking out over predatory journals and open access publishing. Authors Mark Vinyard and Jaimie Beth Colvin, who successfully launched a faculty publishing initiative, explain which aspects of metrics are truly essential to grasp, and they place these numbers in context. They help readers identify the metrics that are the best fit for their scholarship and give librarians and professors the tools to make smart decisions in this changing scholarly metrics landscape.

Unique Researcher IDs

Due to common researcher names, name changes, cultural differences in name order, and inconsistent use of middle initials, it can be difficult to accurately calculate measures of personal impact. Numeric codes can help identify individual researchers.

ORCID (Open Researcher and Contributor ID)

ResearcherID (Clarivate Analytics)

Scopus Author Profile is a unique record of that researcher’s publication activity. The details come from peer-reviewed articles and other publications that are indexed in Scopus. Create your free account with Elsevier (vendor for Scopus, Embase, Clinical Key) to edit your profile.

Google Scholar

You can set up your own Google Scholar Profile! Please note you must have at least one manuscript published.

Google Scholar calculates several different metrics based on the h-index of a publication (not the author's).

h-index

"For the few scientists who earn a Nobel Prize, the impact...of their research is unquestionable. For the rest of us, how does one quantify the cumulative impact of an individual's scientific research output?" -- J.E. Hirsch 2005

Your productivity as a researcher can be measured by your total number of articles, and the impact of your research can be measured by the total number of times your articles have been cited. The h-index (AKA Hirsch index) is a combined measure of both productivity and impact. An index of h means that your h most highly-cited articles have at least h citations each.

The h-index is more informative than total number of articles (which ignores how well those articles have been received by other researchers) or total number of citations (which can be inordinately influenced by a small number of highly-cited articles and therefore not an accurate reflection of productivity).

One caveat about the h-index is that it correlates with the length of a researcher's career (i.e., researchers who have been publishing for longer tend to have higher h-indices). It can also be inflated by self-citation. In addition, the h-index ignores the order of authorship, which is very important in some disciplines. Additionally, because different disciplines have different publishing practices, the h-index should not be used to compare researchers across different disciplines. Average impact scores vary widely from discipline to discipline.

iCite for Author Metrics

iCite provides bibliometric information for journal articles that have been included in the PubMed database. Citation data are drawn from: PubMed Central, European PubMed Central, CrossRef, and Web of Science. At present, only PubMed citations are included, so citations appearing from journals outside PubMed are not counted.

For an analysis by author, the following data will be produced:

Total number of articles within PubMed (Total Pubs)
Mean number of articles published per year (Pubs/Year)
Number of citations for the articles (Cites/Year): maximum, mean, standard error of the mean, and median
Relative Citation Ratio (RCR): maximum, mean, standard error of the mean, and median
Weighted RCR: the sum of the RCRs for the articles within the analysis group
The Relative Citation Ratio (RCR) is a NIH metric representing a citation-based measure of scientific influence. It is calculated as the cites/year of each paper, normalized to the citations per year received by NIH-funded papers in the same field and year. A paper with an RCR of 1.0 has received the same number of cites/year as the median NIH-funded paper in its field, while a paper with an RCR of 2.0 has received twice as many cites/year as the median NIH-funded paper in its field.