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Model of the Dynamic Construction Process of Texts and Scaling Laws of Words Organization in Language Systems

Author

Listed:
  • Shan Li
  • Ruokuang Lin
  • Chunhua Bian
  • Qianli D Y Ma
  • Plamen Ch Ivanov

Abstract

Scaling laws characterize diverse complex systems in a broad range of fields, including physics, biology, finance, and social science. The human language is another example of a complex system of words organization. Studies on written texts have shown that scaling laws characterize the occurrence frequency of words, words rank, and the growth of distinct words with increasing text length. However, these studies have mainly concentrated on the western linguistic systems, and the laws that govern the lexical organization, structure and dynamics of the Chinese language remain not well understood. Here we study a database of Chinese and English language books. We report that three distinct scaling laws characterize words organization in the Chinese language. We find that these scaling laws have different exponents and crossover behaviors compared to English texts, indicating different words organization and dynamics of words in the process of text growth. We propose a stochastic feedback model of words organization and text growth, which successfully accounts for the empirically observed scaling laws with their corresponding scaling exponents and characteristic crossover regimes. Further, by varying key model parameters, we reproduce differences in the organization and scaling laws of words between the Chinese and English language. We also identify functional relationships between model parameters and the empirically observed scaling exponents, thus providing new insights into the words organization and growth dynamics in the Chinese and English language.

Suggested Citation

  • Shan Li & Ruokuang Lin & Chunhua Bian & Qianli D Y Ma & Plamen Ch Ivanov, 2016. "Model of the Dynamic Construction Process of Texts and Scaling Laws of Words Organization in Language Systems," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-12, December.
    • Handle: RePEc:plo:pone00:0168971
    DOI: 10.1371/journal.pone.0168971
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    References listed on IDEAS

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    1. Plamen Ch Ivanov & Ainslie Yuen & Pandelis Perakakis, 2014. "Impact of Stock Market Structure on Intertrade Time and Price Dynamics," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-14, April.
    2. Blank, Aharon & Solomon, Sorin, 2000. "Power laws in cities population, financial markets and internet sites (scaling in systems with a variable number of components)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(1), pages 279-288.
    3. Ebeling, Werner & Neiman, Alexander, 1995. "Long-range correlations between letters and sentences in texts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 215(3), pages 233-241.
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