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Detecting evolutionary forces in language change

Nature volume 551, pages 223–226 (2017)Cite this article

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Abstract

Both language and genes evolve by transmission over generations with opportunity for differential replication of forms1. The understanding that gene frequencies change at random by genetic drift, even in the absence of natural selection, was a seminal advance in evolutionary biology2. Stochastic drift must also occur in language as a result of randomness in how linguistic forms are copied between speakers3,4. Here we quantify the strength of selection relative to stochastic drift in language evolution. We use time series derived from large corpora of annotated texts dating from the 12th to 21st centuries to analyse three well-known grammatical changes in English: the regularization of past-tense verbs5,6,7,8,9, the introduction of the periphrastic ‘do’10, and variation in verbal negation11. We reject stochastic drift in favour of selection in some cases but not in others. In particular, we infer selection towards the irregular forms of some past-tense verbs, which is likely driven by changing frequencies of rhyming patterns over time. We show that stochastic drift is stronger for rare words, which may explain why rare forms are more prone to replacement than common ones6,9,12. This work provides a method for testing selective theories of language change against a null model and reveals an underappreciated role for stochasticity in language evolution.

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Figure 1: A null model of language change.
Figure 2: Verb regularization and irregularization.
Figure 3: The rise of the periphrastic ‘do’ in Early Modern English.
Figure 4: Evolution of verbal negation.

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Acknowledgements

We thank H. Bacovcin, T. Kroch, and M. Liberman. R.C. acknowledges support from the University of Pennsylvania Research Foundation. J.B.P. acknowledges support from the David & Lucile Packard Foundation, the US Defense Advanced Research Projects Agency (D12AP00025), and the US Army Research Office (W911NF-12-1-0552).

Author information

Author notes

  1. Mitchell G. Newberry and Christopher A. Ahern: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Biology, University of Pennsylvania, Philadelphia, 19104, Pennsylvania, USA

    Mitchell G. Newberry & Joshua B. Plotkin

  2. Department of Linguistics, University of Pennsylvania, Philadelphia, 19104, Pennsylvania, USA

    Christopher A. Ahern & Robin Clark

Authors
  1. Mitchell G. Newberry
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  2. Christopher A. Ahern
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  4. Joshua B. Plotkin
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Contributions

M.G.N., C.A.A., R.C., and J.B.P. conceived the study, designed the analysis, and wrote the paper.

Corresponding author

Correspondence to Joshua B. Plotkin.

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The authors declare no competing financial interests.

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Reviewer Information Nature thanks R. A. Bentley and the other anonymous reviewers for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Figure 1 Time series of changing rhyming patterns.

Each panel shows the time series of a polymorphic verb (black lines), repeated from Fig. 2a, and the frequency of similar-sounding monomorphic regular (orange) and irregular (blue) verbs in the Corpus of Historical American English. The tokens included are all tenses of those lemmas that possess a pronunciation known to the Carnegie Mellon University Pronouncing Dictionary in both the lemma and the simple past tense. The list of verbs incorporated in each time series is given in Extended Data Table 2. For 17 polymorphic verbs we find no similar-sounding monomorphic irregular verbs (all-orange panels). The title of each panel indicates the sign of the maximum-likelihood selection coefficient, either regular → irregular or irregular → regular.

Extended Data Table 1 FIT results for past-tense verbs
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Extended Data Table 2 List of similar-sounding monomorphic verbs for each past-tense conjugation of polymorphic verbs
Full size table
Extended Data Table 3 FIT results for do-support
Full size table

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Supplementary Information

This file contains supplementary text S1.1 – S1.7 and Figure S1 - Temporal trends in the usage of 36 verbs, in the simple past tense and in all tenses. (PDF 371 kb)

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Newberry, M., Ahern, C., Clark, R. et al. Detecting evolutionary forces in language change. Nature 551, 223–226 (2017). https://doi.org/10.1038/nature24455

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