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Letters to Nature
Nature 178, 1308 (08 December 1956); doi:10.1038/1781308a0
A Theory of Word-Frequency Distribution
A. F. PARKER-RHODES & T. JOYCE
Cambridge Language Research Unit, 20 Millington Road, Cambridge.
THE object of this communication is to show that a certain remarkably simple experimental relation governing word-frequencies in language can be explained by a simple model of the process of searching for information, about each word heard or read, in the memory of words employed in the language faculty.
Cover, T. King, R.
Abstract
In his original paper on the subject, Shannon found upper and lower bounds for the entropy of printed English based on the number of trials required for a subject to guess subsequent symbols in a given text. The guessing approach precludes asymptotic consistency of either the upper or lower bounds except for degenerate ergodic processes. Shannon's technique of guessing the next symbol is altered by having the subject place sequential bets on the next symbol of text.....
Damián Zanette Marcelo Montemurro
Abstract
We investigate the origin of Zipf's law for words in written texts by means of a stochastic dynamic model for text generation. The model incorporates both features related to the general structure of languages and memory effects inherent to the production of long coherent messages in the communication process. It is shown that the multiplicative dynamics of our model lead to rank-frequency distributions in quantitative agreement with empirical data. Our results give support to the linguistic relevance of Zipf's law in human language.
Le Quan Ha Queen's University of Belfast, Belfast, Northern Ireland
E. I. Sicilia-Garcia Ji Ming F. J. Smith
Zipf's law states that the frequency of word tokens in a large corpus of natural language is inversely proportional to the rank. The law is investigated for two languages English and Mandarin and for n-gram word phrases as well as for single words. The law for single words is shown to be valid only for high frequency words. However, when single word and n-gram phrases are combined together in one list and put in order of frequency the combined list follows Zipf's law accurately for all words and phrases, down to the lowest frequencies in both languages. The Zipf curves for the two languages are then almost identical.