Invented by Jorge Hirsch in 2005, the H-index quantifies the output of an individual researcher. It addresses problems with using total number of articles or total citations as an indicator of impact and it can be a useful metric because it discounts the disproportionate weight of highly cited papers.
It is worked out by ranking the researcher’s papers in descending order of how many times each has been cited. The value of H is equal to the number of papers in the list that have that same number or more citations.
For example:
Title 1 cited 1177 times
Title 2 cited 721 times
Title 3 cited 717 times
…
Title 55 cited 71 times
Title 66 cited 69 times
Title 67 cited 67 times
------------------------------------------------------------------ h index = 67
Title 68 cited 67 times
A researcher's H-index may vary from one database to another. Scopus, Web of Science and Google Scholar, for example, all look at slightly different sets of publications, and consequently citation counts will be different.
The H-index is also biased against researchers with a short career and it does not take into account self-cites, review articles, or co-authors
The M-quotient is calculated by dividing the h-index by the number of research active years (taken from publication date of first article).
For example
Researcher |
H-index |
Years active |
M-quotient |
a |
50 |
25 |
2 |
b |
30 |
10 |
3 |
The issues with this are: the first publication may well have been a small publication as a co-author, long before the researcher started publishing more regularly. It discriminates against people who have taken career breaks, or work part time, and therefore it is more likely to adversely impact on women.
The h-index is not a useful metric for early career researchers, amongst other criticisms of its usefulness. Some alternative metrics you might want to consider include: