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Quantifying the evolutionary dynamics of language

Author

Listed:
  • Erez Lieberman

    (Program for Evolutionary Dynamics
    Harvard University, Cambridge, Massachusetts 02138, USA
    Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA)

  • Jean-Baptiste Michel

    (Program for Evolutionary Dynamics
    Harvard Medical School, Boston, Massachusetts 02115, USA)

  • Joe Jackson

    (Program for Evolutionary Dynamics)

  • Tina Tang

    (Program for Evolutionary Dynamics)

  • Martin A. Nowak

    (Program for Evolutionary Dynamics)

Abstract

Words on the brink As a language evolves, grammatical rules emerge and exceptions die out. Lieberman et al. have calculated the rate at which a language grows more regular, based on 1,200 years of English usage. Of 177 irregular verbs, 79 became regular in the last millennium. And the trend follows a simple rule: a verb's half-life scales as the square root of its frequency. Irregular verbs that are 100 times as rare regularize 10 times faster. The emergence of a rule (such as adding –ed for the past tense) spells death for exceptional forms. The cover graphic makes the point: verb size corresponds to usage frequency, so large verbs stay at the top, and small verbs fall to the bottom. 'Wed', the next irregular verb to go, is on the brink. In a separate study, Pagel et al. looked at changing word meanings. Across the Indo-European languages, words like 'tail' or 'bird' evolve rapidly and are expressed by many unrelated words. Others, like 'two', are expressed by closely related word forms across the whole language family. Data from over 80 modern languages show that the more a word is used, the less it changes.

Suggested Citation

  • Erez Lieberman & Jean-Baptiste Michel & Joe Jackson & Tina Tang & Martin A. Nowak, 2007. "Quantifying the evolutionary dynamics of language," Nature, Nature, vol. 449(7163), pages 713-716, October.
    • Handle: RePEc:nat:nature:v:449:y:2007:i:7163:d:10.1038_nature06137
    DOI: 10.1038/nature06137
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    Cited by:

    1. Alberto Acerbi & Vasileios Lampos & Philip Garnett & R Alexander Bentley, 2013. "The Expression of Emotions in 20th Century Books," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-6, March.
    2. Shimpei Okuda & Michio Hosaka & Kazutoshi Sasahara, 2023. "Detecting directional forces in the evolution of grammar: A case study of the English perfect with intransitives across EEBO, COHA, and Google Books," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-8, December.
    3. Animesh Mukherjee & Francesca Tria & Andrea Baronchelli & Andrea Puglisi & Vittorio Loreto, 2011. "Aging in Language Dynamics," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-7, February.
    4. Xueying Liu & Haoran Zhu & Lei Lei, 2022. "Dependency distance minimization: a diachronic exploration of the effects of sentence length and dependency types," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.
    5. Tyler J Gray & Andrew J Reagan & Peter Sheridan Dodds & Christopher M Danforth, 2018. "English verb regularization in books and tweets," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-17, December.
    6. Liang Xu & Min Xu & Zehua Jiang & Xin Wen & Yishan Liu & Zaoyi Sun & Hongting Li & Xiuying Qian, 2023. "How have music emotions been described in Google books? Historical trends and corpus differences," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    7. Damian Ruck & R. Alexander Bentley & Alberto Acerbi & Philip Garnett & Daniel J. Hruschka, 2017. "Role Of Neutral Evolution In Word Turnover During Centuries Of English Word Popularity," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 20(06n07), pages 1-16, September.
    8. Zhiwen Hu & Yiping Cui & Jian Zhang & Jacqueline Eviston-Putsch, 2020. "Shalosh B. Ekhad: a computer credit for mathematicians," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 71-97, January.
    9. David Bodoff & Ron Bekkerman & Julie Dai, 2017. "Evolution of language: An empirical study at eBay Big Data Lab," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-17, December.
    10. R Alexander Bentley & Alberto Acerbi & Paul Ormerod & Vasileios Lampos, 2014. "Books Average Previous Decade of Economic Misery," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-7, January.
    11. Jean-Marc Luck & Anita Mehta, 2023. "Evolution of grammatical forms: some quantitative approaches," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(2), pages 1-15, February.
    12. Bradley Voytek, 2016. "The Virtuous Cycle of a Data Ecosystem," PLOS Computational Biology, Public Library of Science, vol. 12(8), pages 1-6, August.
    13. Heng Chen & Junying Liang & Haitao Liu, 2015. "How Does Word Length Evolve in Written Chinese?," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-12, September.
    14. Charlie Pilgrim & Weisi Guo & Thomas T. Hills, 2021. "The Rising Entropy of English in the Attention Economy," Papers 2107.12848, arXiv.org, revised Apr 2023.
    15. Eduardo G Altmann & Janet B Pierrehumbert & Adilson E Motter, 2011. "Niche as a Determinant of Word Fate in Online Groups," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-12, May.
    16. Parshad, Rana D. & Bhowmick, Suman & Chand, Vineeta & Kumari, Nitu & Sinha, Neha, 2016. "What is India speaking? Exploring the “Hinglish” invasion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 375-389.
    17. Zejie Zhou & Boleslaw K Szymanski & Jianxi Gao, 2020. "Modeling competitive evolution of multiple languages," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-16, May.

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