1 - 10 of 25 Chapters
[For nearly hundred years, researchers have noticed how language ubiquitously follows certain mathematical properties. These properties differ from linguistic universals that contribute to describing the variation of human languages. Rather, they are statistical: they can only be identified by...
[As this book is about the universal properties of language, this chapter explains and organizes different approaches taken with respect to the notion of universals. A universal of language is defined as a property that holds across all kinds of natural language on Earth. The chapters in Parts...
[The previous chapter was dedicated to considering the background of this book from the viewpoint of universals. It involved notions originating in the humanities, especially linguistics and philosophy. Because language is a system to represent meaning, the analysis to acquire those linguistic...
[Part II mainly considers the characteristics of a population of linguistic elements, such as words. A word has a frequency in a text, and the vocabulary of the text forms a population, which this part analyzes.]
[As shown at the end of the previous chapter, the rank-frequency relation of Moby Dick almost follows a power law -> with an η value close to 1. The goal of this chapter is to see how well Zipf’s law holds among various kinds of texts and data. A text is typically written by a single author, but...
[This last chapter of Part II further considers the nature of a vocabulary population in terms of two related properties that have a mathematical relation with Zipf’s law: the density function and the vocabulary growth. Similarly to Zipf’s law, both nearly indicate power-law behavior but are...
[Part II investigated the population of words, but the book thus far has not considered the properties underlying a sequence of words. Language forms a sequence, which characterizes what language is. Indeed, Sect. 4.4 showed that, for n-grams, the subsequences of natural language texts present a...
[The previous chapter examined the return distributions of the words in a text. Another way to examine returns is in terms of how they succeed one another. As we will see here and in the following chapter, in a natural language text, a short return is likely to follow a series of short returns,...
[The previous two chapters presented analyses based on return intervals. Chapter 7 was about the distribution of returns, whereas Chap. 8 considered sequences of returns.]
[We now have a rough overview of the most important statistical universals underlying language. As a whole, is there any way to examine how complex language is? What is the characteristic underlying this complexity?]
Read and print from thousands of top scholarly journals.
Continue with Facebook
Log in with Microsoft
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Sign Up Log In
To subscribe to email alerts, please log in first, or sign up for a DeepDyve account if you don’t already have one.
To get new article updates from a journal on your personalized homepage, please log in first, or sign up for a DeepDyve account if you don’t already have one.