Abstract
Words are built from smaller meaning bearing parts, called morphemes. As one word can contain multiple morphemes, one morpheme can be present in different words. The number of distinct words a morpheme can be found in is its family size. Here we used Birth-Death-Innovation Models (BDIMs) to analyze the distribution of morpheme family sizes in English and German vocabulary over the last 200 years. Rather than just fitting to a probability distribution, these mechanistic models allow for the direct interpretation of identified parameters. Despite the complexity of language change, we indeed found that a specific variant of this pure stochastic model, the second order linear balanced BDIM, significantly fitted the observed distributions. In this model, birth and death rates are increased for smaller morpheme families. This finding indicates an influence of morpheme family sizes on vocabulary changes. This could be an effect of word formation, perception or both. On a more general level, we give an example on how mechanistic models can enable the identification of statistical trends in language change usually hidden by cultural influences.
Highlights
New words can be based on the new association of a string to a meaning, they can be loaned from another language [2] or they can be derived from already existing words
We found that new words are preferentially built with morphemes which are not already present in many words [8]
Thereby, we look at two processes simultaneously, the formation of a new word and the acceptance of the new word in the community of speakers
Summary
New words can be based on the new association of a string to a meaning, they can be loaned from another language [2] or they can be derived from already existing words The latter is the most frequent process in current Indo-European languages [3]. We found that new words are preferentially built with morphemes which are not already present in many words [8]. Does this tendency have an effect on the vocabulary of a language?
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