Power-law regularities in human language

Ali Mehri () and Sahar Mohammadpour Lashkari
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Ali Mehri: Faculty of Science, Noshirvani University of Technology
Sahar Mohammadpour Lashkari: Faculty of Science, Noshirvani University of Technology

The European Physical Journal B: Condensed Matter and Complex Systems, 2016, vol. 89, issue 11, 1-6

Abstract: Abstract Complex structure of human language enables us to exchange very complicated information. This communication system obeys some common nonlinear statistical regularities. We investigate four important long-range features of human language. We perform our calculations for adopted works of seven famous litterateurs. Zipf’s law and Heaps’ law, which imply well-known power-law behaviors, are established in human language, showing a qualitative inverse relation with each other. Furthermore, the informational content associated with the words ordering, is measured by using an entropic metric. We also calculate fractal dimension of words in the text by using box counting method. The fractal dimension of each word, that is a positive value less than or equal to one, exhibits its spatial distribution in the text. Generally, we can claim that the Human language follows the mentioned power-law regularities. Power-law relations imply the existence of long-range correlations between the word types, to convey an especial idea.

Keywords: Statistical; and; Nonlinear; Physics (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (6)

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DOI: 10.1140/epjb/e2016-70423-9

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