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A COMPARISON OF TWO FLUCTUATION ANALYSES FOR NATURAL LANGUAGE CLUSTERING PHENOMENA —TAYLOR vs. EBELING & NEIMAN METHODS—

Author

Listed:
  • KUMIKO TANAKA-ISHII

    (Research Center for Advanced Science and Technology, University of Tokyo, Japan)

  • SHUNTARO TAKAHASHI

    (Research Center for Advanced Science and Technology, University of Tokyo, Japan)

Abstract

This paper considers the fluctuation analysis methods of Taylor and Ebeling & Neiman. While both have been applied to various phenomena in the statistical mechanics domain, their similarities and differences have not been clarified. After considering their analytical aspects, this paper presents a large-scale application of these methods to text. It is found that both methods can distinguish real text from independently and identically distributed (i.i.d.) sequences. Furthermore, it is found that the Taylor exponents acquired from words can roughly distinguish text categories; this is also the case for Ebeling and Neiman exponents, but to a lesser extent. Additionally, both methods show some possibility of capturing script kinds.

Suggested Citation

  • Kumiko Tanaka-Ishii & Shuntaro Takahashi, 2021. "A COMPARISON OF TWO FLUCTUATION ANALYSES FOR NATURAL LANGUAGE CLUSTERING PHENOMENA —TAYLOR vs. EBELING & NEIMAN METHODS—," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 29(02), pages 1-16, March.
  • Handle: RePEc:wsi:fracta:v:29:y:2021:i:02:n:s0218348x2150033x
    DOI: 10.1142/S0218348X2150033X
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