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The H-Index is the largest number h such that h papers each have at least h citations. Sort your papers by citation count (highest first), then find the last paper where citations ≥ rank.
| Rank | Citations | Counts for H? |
|---|---|---|
| 1 | 15 | ✓ |
| 2 | 12 | ✓ |
| 3 | 10 | ✓ |
| 4 | 7 | ✓ |
| 5 | 5 | ✓ |
| 6 | 4 | ✗ |
| 7 | 2 | ✗ |
H-Index = 5 — five papers have at least 5 citations. Paper 6 has only 4 citations, which is less than its rank of 6.
Want to see whether your H-Index is above average? Compare it against 2026 field benchmarks →
H-Index
Number of papers with ≥h citations each. Balances productivity and impact
G-Index
Largest g where top g papers have ≥ g² citations total. Rewards breakthroughs
i10-Index
Count of papers with ≥10 citations. Simple but less nuanced than H
Total Citations
Raw citation count — useful for absolute impact but skewed by single papers
The Number That Defines Academic Careers
An H-index of 20 means 20 papers, each cited at least 20 times — a mark of sustained, citable contribution to a field. It's imperfect, but it's the benchmark that hiring committees reach for first.
How the H-Index Works
The H-index measures both a researcher's productivity and citation impact in a single number. An H-index of 10 means you have 10 papers that have each received at least 10 citations — a strong signal of consistent scholarly influence rather than a single viral paper.
Practical example: You have 7 papers with citation counts of 15, 9, 7, 5, 4, 3, and 1 (sorted descending). Paper 5 has 4 citations — rank 5 ≥ 4, so it counts. Paper 6 has 3 citations — rank 6 > 3, so it doesn't. Your H-index is 5.
H-Index vs. G-Index: H treats every qualifying paper equally. The G-index rewards breakthrough papers by finding the largest g where your top g papers have ≥ g² citations total. → Calculate your G-Index
What Is a Good H-Index?
Early career (1–10 years) — H = 2–15
A new researcher with H = 5 has published meaningfully. H = 10+ in your first decade signals rapid impact. Fields vary: hard sciences accelerate faster than humanities.
Mid-career (10–25 years) — H = 15–30
H = 20 is a strong signal for tenure and promotion in most STEM disciplines. Social scientists/humanities: H = 10–15 mid-career is competitive. Nobel laureates typically have H = 45–50+.
Database matters — varies by 2–5 points
Google Scholar is broadest (usually highest H); Web of Science most selective; Scopus between. For official assessments, WoS or Scopus are typically required. For self-reporting, Scholar is most inclusive.
Frequently Asked Questions
Formula & Calculation Method
H-Index (Hirsch Index)
h = max{h : top h papers each have ≥ h citations}
h— Largest integer such that the researcher has h papers each cited at least h times
Source: Hirsch, J. E. (2005). PNAS 102(46): 16569–16572
G-Index
g = max{g : top g papers together have ≥ g² citations}
g— G-Index — accounts for highly-cited outliers that H-Index ignores
Source: Egghe, L. (2006). Scientometrics 69(1): 131–152
i10-Index
i10 = count(papers with ≥ 10 citations)
i10— Number of publications with at least 10 citations (Google Scholar metric)
Source: Google Scholar (introduced 2011)
Authoritative Sources & Standards
- NSF: NSF Biographical Sketch requirements (PAPPG 2024) include H-Index as an acceptable productivity metric in academic grant applications. → NSF
- NIH: NIH Biosketch (revised 2021) allows citation metrics including H-Index in Section C 'Contributions to Science', though discourages over-reliance on single metrics. → NIH
Expert Insights & Research
A successful researcher's H-Index approximately equals years since first publication (Hirsch, 2005). H = 20 indicates a senior, well-established scientist; H = 40+ characterizes National Academy members in most STEM fields.
H-Index discriminates against young researchers (cannot exceed publication count) and rewards publication breadth over depth. Field normalization (e.g., FWCI from Scopus) is recommended for cross-disciplinary comparison.
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For informational purposes only — not financial, medical, or legal advice. Results are estimates; use at your own risk. Full terms