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Intermittency and scale-free networks: a dynamical model for human language complexity

Paolo Allegrini·Paolo Grigolini·Luigi Palatella
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Abstract

In this paper we try to model certain features of human language complexity by means of advanced concepts borrowed from statistical mechanics. We use a time series approach, the diffusion entropy method (DE), to 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 network complexity is independently measured on the same corpus, looking at the co-occurrence of nouns and verbs. This connection of cognitive complexity with long-range time correlations also provides an explanation for the famous Zipf's law in terms of the generalized central limit theorem.

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Paolo Allegrini, Paolo Grigolini, Luigi Palatella. 2003-10-28. Intermittency and scale-free networks: a dynamical model for human language complexity. https://doi.org/10.1016/s0960-0779(03)00432-6

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