Abstract
Human language is based on grammatical rules1,2,3,4. Cultural evolution allows these rules to change over time5. Rules compete with each other: as new rules rise to prominence, old ones die away. To quantify the dynamics of language evolution, we studied the regularization of English verbs over the past 1,200 years. Although an elaborate system of productive conjugations existed in English’s proto-Germanic ancestor, Modern English uses the dental suffix, ‘-ed’, to signify past tense6. Here we describe the emergence of this linguistic rule amidst the evolutionary decay of its exceptions, known to us as irregular verbs. We have generated a data set of verbs whose conjugations have been evolving for more than a millennium, tracking inflectional changes to 177 Old-English irregular verbs. Of these irregular verbs, 145 remained irregular in Middle English and 98 are still irregular today. We study how the rate of regularization depends on the frequency of word usage. The half-life of an irregular verb scales as the square root of its usage frequency: a verb that is 100 times less frequent regularizes 10 times as fast. Our study provides a quantitative analysis of the regularization process by which ancestral forms gradually yield to an emerging linguistic rule.
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Acknowledgements
This work was supported by the John Templeton Foundation and by a grant from the NSF-NIH joint programme in mathematical biology. The Program for Evolutionary Dynamics is sponsored by J. Epstein. E.L. was supported by the National Defense Science and Engineering Graduate Fellowship and the National Science Foundation Graduate Fellowship. We thank S. Pinker, J. Rau, D. Donoghue and A. Presser for discussions, and J. Saragosti for help with visualization.
Author information
Author notes
- Erez Lieberman
- & Jean-Baptiste Michel
These authors contributed equally to this work
Affiliations
Program for Evolutionary Dynamics, Department of Organismic and Evolutionary Biology, Department of Mathematics,
- Erez Lieberman
- , Jean-Baptiste Michel
- , Joe Jackson
- , Tina Tang
- & Martin A. Nowak
Department of Applied Mathematics, Harvard University, Cambridge, Massachusetts 02138, USA
- Erez Lieberman
Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
- Erez Lieberman
Department of Systems Biology, Harvard Medical School, Boston, Massachusetts 02115, USA
- Jean-Baptiste Michel
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Competing interests
The authors declare no competing financial interests.
Corresponding author
Correspondence to Erez Lieberman.
Supplementary information
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Supplementary Information
This file contains the main Supplementary Information for the paper with Supplementary Tables 1-7 and Supplementary Figures S1-S2 with Legends. It includes a table of all the irregular verbs found, as well as their frequency and relevant source text. It also provides a description of the Irregular equation, and Supplementary Discussion of the dynamics within rules and of changes in frequency since Middle English with additional references.
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This file contains Supplementary Data which is a tab-delimited text file containing all of the source data.
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Supplementary Zip File
This file is a zipped version of all the Python source code, enabling the reader to browse the code and reproduce the results using the Supplementary Data as the sole input.
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Further reading
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Detecting evolutionary forces in language change
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Mathematical Modeling of Learning from an Inconsistent Source: A Nonlinear Approach
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When Learners Surpass Their Models: Mathematical Modeling of Learning from an Inconsistent Source
Bulletin of Mathematical Biology (2014)
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Erfahrung zählt. Frequenzeff ekte in der Sprache–ein Werkstattbericht
Zeitschrift für Literaturwissenschaft und Linguistik (2013)
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