Types, Tokens, and Hapaxes: A New Heap's Law
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Abstract (arXiv)
Heap's Law states that in a large enough text corpus, the number of types as a function of tokens grows as N=KMβ for some free parameters K,β. Much has been written about how this result and various generalizations can be derived from Zipf's Law. Here we derive from first principles a completely novel expression of the type-token curve and prove its superior accuracy on real text. This expression naturally generalizes to equally accurate estimates for counting hapaxes and higher n-legomena.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 Dec 2018.
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Citing papers per year: 2023: 1; 2024: 0; 2025: 3.
4 papers.
- 2025From Zipf's Law to Neural Scaling through Heaps' Law and Hilberg's Hypothesis15 Dec 2025
- 2025Quadratic Term Correction on Heaps' Law18 Nov 2025
- 2025From Press to Pixels: Evolving Urdu Text Recognition20 May 2025
- 2023Corrections of Zipf's and Heaps' Laws Derived from Hapax Rate Models24 Jul 2023