Author metrics are used to track how often an author's works are cited and can demonstrate the reach and impact of a researcher's work. Author metrics can be used in funding applications, academic promotions and performance reviews. Author metrics are also used to discover key researchers in a field, track the work of colleagues and identify potential collaborators.

One of the biggest challenges to tracking and analysing an author's impact is having a correct, complete publication list for that author. At GCU we recommend using ORCID as a persistent author identifier and using this identifier whenever you publish.

There are two main citation-based author metrics:

• Citation count, or sum of times cited, is a simple measure of the number of citations a researcher has received for all their published outputs.
• The author h-index, proposed by Hirsch in 2005, measures a researcher’s impact based on the number of citations of their work:
  • h-index = number of papers (h) with a citation number ≥ h
  • Example: If an author has an h-index of 12 it means that out of the total number of published outputs by that author, 12 of those outputs have been cited at least 12 times.

These metrics can be found on Scopus, Web of Science and Google Scholar. The values will likely vary across these sources, based on the content indexed by each of these databases.

Limitations of citation-based author metrics

• These metrics favour experienced authors as they are measures that can only increase over time.
• They favour authors in disciplines with fast publication rates, and with cultures of extensive referencing and multiple authorship.
• Varying coverage of citation indexes means these metrics can differ significantly from one bibliometric database to another. Coverage of monographs, chapters and non-English language outputs are poorly represented in some databases.
• These metrics take no account of the number of authors on an output or the contribution each author made to the research. They will also count negative citations positively.
• The h-index ignores small numbers of important articles. Highly cited articles are likely to be the most important, but their importance is reduced as the score increases only as citations and publications accumulate.
• There is not an easy way to know what a “good” h-index is in a certain discipline, and no way to compare across disciplines.

Using author metrics responsibly

• Ensure you have curated your online profile on the database you are going to use – Scopus, Web of Science or Google Scholar.
• Check your author metrics on each of the databases to see which gives you the highest score. State the source you used and the date it was calculated so that it can be replicated and/or defended if necessary.
• Get a feel for what is a “good” author metric in your field. Check the metrics of colleagues in your discipline who are at a similar career stage to yourself. Never compare these author metrics across disciplines and different career stages.
• Include other data. Don’t just rely on one measure to encapsulate your entire research career. Include contextual information, for example details of the number of outputs you have published in your career or a paper that has been very highly cited which is not adequately represented by your h-index.
• Challenge the use of these metrics and understand their limitations.