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We model certain features of human language complexity by means of advancedconcepts borrowed from statistical mechanics. Using a time series approach, thediffusion entropy method (DE), we compute the complexity of an Italian corpusof newspapers and magazines. We find that the anomalous scaling index iscompatible with a simple dynamical model, a random walk on a complex scale-freenetwork, which is linguistically related to Saussurre's paradigms. The modelyields the famous Zipf's law in terms of the generalized central limit theorem.Comment: Conference FRACTAL 200

COGNITIVE SCALE-FREE NETWORKS AS A MODEL FOR INTERMITTENCY IN HUMAN NATURAL LANGUAGE