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Natural languages are full of rules and exceptions. One of the most famousquantitative rules is Zipf's law which states that the frequency of occurrenceof a word is approximately inversely proportional to its rank. Though this`law' of ranks has been found to hold across disparate texts and forms of data,analyses of increasingly large corpora over the last 15 years have revealed theexistence of two scaling regimes. These regimes have thus far been explained bya hypothesis suggesting a separability of languages into core and non-corelexica. Here, we present and defend an alternative hypothesis, that the twoscaling regimes result from the act of aggregating texts. We observe that textmixing leads to an effective decay of word introduction, which we show providesaccurate predictions of the location and severity of breaks in scaling. Uponexamining large corpora from 10 languages in the Project Gutenberg eBookscollection (eBooks), we find emphatic empirical support for the universality ofour claim.

Text mixing shapes the anatomy of rank-frequency distributions: A modern Zipfian mechanics for natural language