ArticlePloS one2015
Rank diversity of languages: generic behavior in computational linguistics.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Language Statistics at Different Spatial, Temporal, and Grammatical Scales.Entropy (Basel, Switzerland) · 2024Article
- Understanding who talks about what: comparison between the information treatment in traditional media and online discussions.Scientific reports · 2023Article
- Dynamics of ranking.Nature communications · 2022Article
- A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics.Entropy (Basel, Switzerland) · 2020Article
- Guiding the Self-Organization of Cyber-Physical Systems.Frontiers in robotics and AI · 2020Article
- Article
- Multi-level computational methods for interdisciplinary research in the HathiTrust Digital Library.PloS one · 2017Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution rank diversity. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: "heads" consist of words which almost do not change their rank in time, "bodies" are words of general use, while "tails" are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied.
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