Entropy and type-token ratio in gigaword corpora

Pablo Rosillo-Rodes, Maxi San Miguel, David Sanchez
11/15/2024
cs.CLcs.IRphysics.soc-ph

No official code found. Best implementation: pablorosillo/entropy_ttr_gigaword (0 stars, last commit 2025-02-26).

Abstract

There are different ways of measuring diversity in complex systems. In particular, in language, lexical diversity is characterized in terms of the type-token ratio and the word entropy. We here investigate both diversity metrics in six massive linguistic datasets in English, Spanish, and Turkish, consisting of books, news articles, and tweets. These gigaword corpora correspond to languages with distinct morphological features and differ in registers and genres, thus constituting a varied testbed for a quantitative approach to lexical diversity. We unveil an empirical functional relation between entropy and type-token ratio of texts of a given corpus and language, which is a consequence of the statistical laws observed in natural language. Further, in the limit of large text lengths we find an analytical expression for this relation relying on both Zipf and Heaps laws that agrees with our empirical findings.

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pablorosillo/entropy_ttr_gigawordCommunity70%

Codes and corpora for "Entropy and type-token ratio in gigaword corpora" arXiv:2411.10227

00PythonFeb 26, 20251 years ago
cc100corporaentropygigawordgutenberg+1 more

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Cite this paper

@article{rosillorodes2024entropy,
  title  = {Entropy and type-token ratio in gigaword corpora},
  author = {Pablo Rosillo-Rodes and Maxi San Miguel and David Sanchez},
  year   = {2024},
  eprint = {2411.10227},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2411.10227v3}
}

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