Dynamics of text generation with realistic Zipf's distribution

Damian Zanette; Marcelo Montemurro

doi:10.1080/09296170500055293

Dynamics of text generation with realistic Zipf's distribution

Damian Zanette, Marcelo Montemurro

Research output: Contribution to journal › Article › peer-review

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. © Taylor & Francis Group Ltd.

Original language	English
Pages (from-to)	29-40
Number of pages	11
Journal	Journal of Quantitative Linguistics
Volume	12
Issue number	1
DOIs	https://doi.org/10.1080/09296170500055293
Publication status	Published - 2005

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title = "Dynamics of text generation with realistic Zipf's distribution",

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. {\textcopyright} Taylor & Francis Group Ltd.",

author = "Damian Zanette and Marcelo Montemurro",

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AU - Montemurro, Marcelo

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AB - 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. © Taylor & Francis Group Ltd.

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DO - 10.1080/09296170500055293

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EP - 40

JO - Journal of Quantitative Linguistics

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Dynamics of text generation with realistic Zipf's distribution

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