Cognitive Scale-Free Networks as a Model for Intermittency in Human Natural Language

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Paper discussing cognitive scale-free networks as a model for intermittency in human natural language.

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11 p.: ill.

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Allegrini, Paolo; Grigolini, Paolo & Palatella, Luigi 2003.

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Paper discussing cognitive scale-free networks as a model for intermittency in human natural language.

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11 p.: ill.

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This is the pre-print version of the paper.

Abstract: We model certain features of human language complexity by means of advanced concepts borrowed from statistical mechanics. Using a time series approach, the diffusion entropy method (DE), we compute the complexity of an Italian corpus of newspapers and magazines. We find that the anomalous scaling index is compatible with a simple dynamical model, a random walk on a complex scale-free network, which is linguistically related to Saussurre's paradigms. The model yields the famous Zipf's law in terms of the generalized central limit theorem.

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  • arXiv: cond-mat/0311314

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  • 2003

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  • July 24, 2013, 1:20 p.m.

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  • March 27, 2014, 3:44 p.m.

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Allegrini, Paolo; Grigolini, Paolo & Palatella, Luigi. Cognitive Scale-Free Networks as a Model for Intermittency in Human Natural Language, paper, 2003; (digital.library.unt.edu/ark:/67531/metadc174698/: accessed November 19, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Arts and Sciences.