How to calculate the h-index step by step

Proposed by Jorge Hirsch in 2005, the h-index balances volume and reception: an author with h = 12 has twelve works cited twelve times or more. Publishing a lot without being cited does not raise it, and a single highly cited paper does not either.

That double condition explains its popularity and its main bias: it grows slowly and penalises short careers, so comparing a doctoral student with a full professor tells you nothing useful.

List every work with its citation count and sort them from highest to lowest. Walk down the list assigning a rank to each work: 1, 2, 3, and so on.

Your h-index is the last rank where the citation count is still greater than or equal to the rank. If work number 9 has 11 citations and number 10 has 7, your h-index is 9.

Doing it by hand once is worth the effort: it shows which works are holding the indicator up and which are one or two citations away from raising it.

Every database indexes a different set of venues and counts citations differently. Google Scholar includes proceedings, chapters, theses and preprints, so it usually reports the highest value. Web of Science and Scopus are stricter, giving lower but more consistent figures.

OpenAlex, the open source we use at Explore Labs, offers broad coverage and lets you reproduce the calculation without a subscription, which matters when you must justify where each number came from.

The other factor is name disambiguation: similar signatures, compound surnames or affiliation changes split one profile into several, and each fragment shows a lower h-index than the real one.

There is no universal threshold, because citation cultures differ widely: biomedicine cites more and sooner than mathematics or the humanities, where the book may be the main vehicle.

To account for career length, the m-quotient divides the h-index by the years since the first publication. Values near 1 are associated with solid trajectories, and values above 2 are rare.

A fair comparison always stays within the same field and similar career lengths; any other use of the indicator invites wrong conclusions.

Add the i10 count (works with ten or more citations), total citations, mean citations per work and the time distribution of your output. Together they show whether impact is recent or old, concentrated or spread.

Promotion files also weigh journal quartiles, leadership (first or corresponding authorship) and the co-authorship network, because those document scientific independence rather than sheer volume.