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Long-Range Correlations in Sentence Series from A Story of the Stone

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  • Tianguang Yang
  • Changgui Gu
  • Huijie Yang

Abstract

A sentence is the natural unit of language. Patterns embedded in series of sentences can be used to model the formation and evolution of languages, and to solve practical problems such as evaluating linguistic ability. In this paper, we apply de-trended fluctuation analysis to detect long-range correlations embedded in sentence series from A Story of the Stone, one of the greatest masterpieces of Chinese literature. We identified a weak long-range correlation, with a Hurst exponent of 0.575±0.002 up to a scale of 104. We used the structural stability to confirm the behavior of the long-range correlation, and found that different parts of the series had almost identical Hurst exponents. We found that noisy records can lead to false results and conclusions, even if the noise covers a limited proportion of the total records (e.g., less than 1%). Thus, the structural stability test is an essential procedure for confirming the existence of long-range correlations, which has been widely neglected in previous studies. Furthermore, a combination of de-trended fluctuation analysis and diffusion entropy analysis demonstrated that the sentence series was generated by a fractional Brownian motion.

Suggested Citation

  • Tianguang Yang & Changgui Gu & Huijie Yang, 2016. "Long-Range Correlations in Sentence Series from A Story of the Stone," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-11, September.
    • Handle: RePEc:plo:pone00:0162423
    DOI: 10.1371/journal.pone.0162423
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    References listed on IDEAS

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    1. Ausloos, M., 2012. "Measuring complexity with multifractals in texts. Translation effects," Chaos, Solitons & Fractals, Elsevier, vol. 45(11), pages 1349-1357.
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    Cited by:

    1. Heng Chen & Haitao Liu, 2018. "Quantifying Evolution of Short and Long-Range Correlations in Chinese Narrative Texts across 2000 Years," Complexity, Hindawi, vol. 2018, pages 1-12, February.
    2. Liu, Yang & Zhuo, Xuru & Zhou, Xiaozhu, 2024. "Multifractal analysis of Chinese literary and web novels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
    3. Ghosh, Dipak & Chakraborty, Sayantan & Samanta, Shukla, 2019. "Study of translational effect in Tagore’s Gitanjali using Chaos based Multifractal analysis technique," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1343-1354.
    4. Yuan, Qianshun & Semba, Sherehe & Zhang, Jing & Weng, Tongfeng & Gu, Changgui & Yang, Huijie, 2021. "Multi-scale transition matrix approach to time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    5. Yue Yang & Changgui Gu & Qin Xiao & Huijie Yang, 2017. "Evolution of scaling behaviors embedded in sentence series from A Story of the Stone," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-14, February.
    6. Vieira, Denner S. & Picoli, Sergio & Mendes, Renio S., 2018. "Robustness of sentence length measures in written texts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 749-754.

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