Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift. Proc R Soc B. 277: 429-436

Department of Psychology, 3210 Tolman Hall, MC 1650, University of California at Berkeley, Berkeley, CA 94720-1650, USA.
Proceedings of the Royal Society B: Biological Sciences (Impact Factor: 5.05). 10/2009; 277(1680):429-36. DOI: 10.1098/rspb.2009.1513
Source: PubMed


Scientists studying how languages change over time often make an analogy between biological and cultural evolution, with words or grammars behaving like traits subject to natural selection. Recent work has exploited this analogy by using models of biological evolution to explain the properties of languages and other cultural artefacts. However, the mechanisms of biological and cultural evolution are very different: biological traits are passed between generations by genes, while languages and concepts are transmitted through learning. Here we show that these different mechanisms can have the same results, demonstrating that the transmission of frequency distributions over variants of linguistic forms by Bayesian learners is equivalent to the Wright-Fisher model of genetic drift. This simple learning mechanism thus provides a justification for the use of models of genetic drift in studying language evolution. In addition to providing an explicit connection between biological and cultural evolution, this allows us to define a 'neutral' model that indicates how languages can change in the absence of selection at the level of linguistic variants. We demonstrate that this neutral model can account for three phenomena: the s-shaped curve of language change, the distribution of word frequencies, and the relationship between word frequencies and extinction rates.

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    • "A model of undirected copying was used, for example, to identify social-network arrangements favorable to selection versus random drift in the sorting of variation (Lieberman et al. 2005), and it was also used to show how highly clustered social networks favor the evolution of cooperation (Ohtsuki et al. 2006). Practical applications, with favorable comparison to real-world data, include baby names (Hahn and Bentley 2003), English words (Bentley 2008; Reali and Griffiths 2009), and prehistoric pottery designs (Neiman 1995). "
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    • "Although there were free parameters in the model used for this analysis, these conclusions were found to be independent over the range of values they could reasonably take (see [3] for full details). On the other hand, the quantitative support for neutral evolution provided by Reali and Griffiths [38], namely compatibility with wordfrequency distributions and lexical replacement rates, involved parameter fitting in both cases. According to Gotelli and McGill [24] parameter fitting is problematic because it biases the null hypothesis in favour of being accepted. "
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