Long-range fractal correlations in literary corpora

By Marcelo A. Montemurro, Pedro A. Pury. 2002

106 citations recorded by the source corpus.

In this paper, we analyze the fractal structure of long human language records by mapping large samples of texts onto time series. The particular mapping set up in this work is inspired on linguistic basis in the sense that is retains the word as the fundamental unit of communication. The results confirm that beyond the short-range correlations resulting from syntactic rules acting at sentence level, long-range structures emerge in large written language samples that give rise to long-range correlations in the use of words.

Subfields: Artificial Intelligence, Economics and Econometrics, Molecular Biology, Statistics and Probability, Natural Language Processing

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Citations in the corpus

On the origin of long-range correlations in texts (2012, background): “• Shuffle words Mixing words order kills correlations for scales larger than the maximum word length [6, 7].”
Towards the Quantification of the Semantic Information Encoded in Written Language (2009, background): “In recent years the use of tools drawn from statistical physics has quantitatively revealed rich linguistic structures at many scales, ranging from the domain of syntax to the organisation of whole lexicons and literary corpora [5, 4, 6, 9, 10, 16, 24, 25].”
Languages cool as they expand: Allometric scaling and the decreasing need for new words (2012, background): “Languages, like biological systems demonstrate economies of scale (b < 1) manifesting from a complex dependency structure that mimics a hierarchical “circulatory system” required by the organization of language [33, 41–45] and the limits of the efficiency of the speakers/writers who employ the words”