Heavy tails of distributions of words in literary texts

My paper with Adam Callahan on the almost power-law behavior of the type-token ratio in literary texts has been submitted for publication and is available here:callahan_davis_heavy_tails_final

In this paper we look in some detail at the behavior of the average number of new words in the first $n$ words of a text, as a function of $n$ . Consider replacing each word in a text by a 1 if that word has not appeared previously in the text, and by a 0 if it has appeared previously. The type-token ratio $\rho(n)$ is the average of the 1′s and 0′s up to $n$ . The sequences of 1′s and 0′s we get this way are not independent, and is not equivalent to a sequence of Bernoulli trial. The behavior of $\rho(n)$ as a function of $n$ is that it is almost described by a power law. Basically, a regression of $\log(\rho(n))$ on $log(n)$ gives a straight line with, typically, $r^2\geq 0.95$ . This means there are constants $A, d$ such that $\rho(n) \approx \frac{A}{n^d}$ . When we plot $\rho(n)n^d$ we should get, approximately, a constant. However we do not. Typically we get a plot that, as a function of $n$ , increases relatively rapidly to a maximum and then decreases very slowly.

A real-valued function $f$ of a positive integer variable is slowly varying if $\frac{f(mn)}{f(m)} \to n^k$ as $m \to \infty$ , for some number $k$ . (This is a “soft analysis” definition in Terry Tao’s sense, I believe. In the applications we have in mind it would definitely help to make this a “hard analysis” definition).

Not only, is $\rho(n)$ a slowly varying function, but $\rho(n)n^d$ – with $d$ as above – has a variance that is slowly varying and decaying to 0. We call functions that are slowly varying with a variance that decays to 0 as a power function, ultra-slowly varying. So what we find for literary texts of a variety of lengths, languages and genres, is that there is an index $d$ (dependent on the text) such that $\rho(n)n^d$ is ultra-slowly varying. If the ultra-slowly varying function were a constant we would have a genuine power law, but it isn’t and we don’t.

We find that for the literary texts we examined, there is a point in the text, which we call a turn-over point, beyond which the type-token ratio $\rho(n)$ is very well described by a power law (typically, $r^2 > 0.99$ ) and before which, $\rho(n)$ is better described as a function of the form $\frac{\alpha+\beta log(n)}{n^d}$ .

In this paper we also consider the relative frequency of occurrence of a word in the first $n$ words of a text as an estimate of the word’s probability of occurrence in the text, and consider the Shannon entropy $H(n)$ of the first $n$ words of text. Typically, $H(n)$ increases logarithmically with $n$ .

Heavy tails of distributions of words in literary texts

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