Zipf's law in 50 languages: its structural pattern, linguistic interpretation, and cognitive motivation
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Abstract (arXiv)
Zipf's law has been found in many human-related fields, including language, where the frequency of a word is persistently found as a power law function of its frequency rank, known as Zipf's law. However, there is much dispute whether it is a universal law or a statistical artifact, and little is known about what mechanisms may have shaped it. To answer these questions, this study conducted a large scale cross language investigation into Zipf's law. The statistical results show that Zipf's laws in 50 languages all share a 3-segment structural pattern, with each segment demonstrating distinctive linguistic properties and the lower segment invariably bending downwards to deviate from theoretical expectation. This finding indicates that this deviation is a fundamental and universal feature of word frequency distributions in natural languages, not the statistical error of low frequency words. A computer simulation based on the dual-process theory yields Zipf's law with the same structural pattern, suggesting that Zipf's law of natural languages are motivated by common cognitive mechanisms. These results show that Zipf's law in languages is motivated by cognitive mechanisms like dual-processing that govern human verbal behaviors.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Jul 2018.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 1; 2025: 0; 2026: 3.
9 papers.
- 2022Automatic Speech Recognition Datasets in Cantonese: A Survey and New Datasetcited by 12
- 2024Analyzing The Language of Visual Tokenscited by 12
- 2022LILA-BOTI : Leveraging Isolated Letter Accumulations By Ordering Teacher Insights for Bangla Handwriting Recognitioncited by 3
- 2026A path to natural language through tokenisation and transformerscited by 2
- 2021Zipf's laws of meaning in Catalancited by 0
- 2023ChiSCor: A Corpus of Freely Told Fantasy Stories by Dutch Children for Computational Linguistics and Cognitive Sciencecited by 0
- 2023Dotless Representation of Arabic Text: Analysis and Modelingcited by 0
- 2026Lossless Compression via Chained Lightweight Neural Predictors with Information Inheritancecited by 0
- 2026Latent Terms: Dense Retrievers Contain Trivially Extractable BM25-ready Zipfian Vocabulariescited by 0
- 2026Latent Terms: Dense Retrievers Contain Trivially Extractable BM25-ready Zipfian Vocabularies28 May 2026
- 2026Lossless Compression via Chained Lightweight Neural Predictors with Information Inheritance16 Apr 2026
- 2026A path to natural language through tokenisation and transformers6 Jan 2026
- 2024Analyzing The Language of Visual Tokens7 Nov 2024
- 2023Dotless Representation of Arabic Text: Analysis and Modeling26 Dec 2023
- 2023ChiSCor: A Corpus of Freely Told Fantasy Stories by Dutch Children for Computational Linguistics and Cognitive Science31 Oct 2023
- 2022LILA-BOTI : Leveraging Isolated Letter Accumulations By Ordering Teacher Insights for Bangla Handwriting Recognition23 May 2022
- 2022Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset7 Jan 2022
- 2021Zipf's laws of meaning in Catalan30 Jun 2021