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Stylometry and Numerals Usage: Benford’s Law and Beyond

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  • Andrei V. Zenkov

    (Department of Modelling of Controllable Systems, Ural Federal University, 620002 Ekaterinburg, Russia
    Department of Information Technologies and Statistics, Ural State University of Economics, 620144 Ekaterinburg, Russia)

Abstract

We suggest two approaches to the statistical analysis of texts, both based on the study of numerals occurrence in literary texts. The first approach is related to Benford’s Law and the analysis of the frequency distribution of various leading digits of numerals contained in the text. In coherent literary texts, the share of the leading digit 1 is even larger than prescribed by Benford’s Law and can reach 50 percent. The frequencies of occurrence of the digit 1, as well as, to a lesser extent, the digits 2 and 3, are usually a characteristic the author’s style feature, manifested in all (sufficiently long) literary texts of any author. This approach is convenient for testing whether a group of texts has common authorship: the latter is dubious if the frequency distributions are sufficiently different. The second approach is the extension of the first one and requires the study of the frequency distribution of numerals themselves (not their leading digits). The approach yields non-trivial information about the author, stylistic and genre peculiarities of the texts and is suited for the advanced stylometric analysis. The proposed approaches are illustrated by examples of computer analysis of the literary texts in English and Russian.

Suggested Citation

  • Andrei V. Zenkov, 2021. "Stylometry and Numerals Usage: Benford’s Law and Beyond," Stats, MDPI, vol. 4(4), pages 1-18, December.
    • Handle: RePEc:gam:jstats:v:4:y:2021:i:4:p:60-1068:d:702592
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    References listed on IDEAS

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    1. Matthew A. Cole & David J. Maddison & Liyun Zhang, 2020. "Testing the emission reduction claims of CDM projects using the Benford’s Law," Climatic Change, Springer, vol. 160(3), pages 407-426, June.
    2. Fewster, R. M., 2009. "A Simple Explanation of Benford's Law," The American Statistician, American Statistical Association, vol. 63(1), pages 26-32.
    3. Theoharry Grammatikos & Nikolaos I. Papanikolaou, 2021. "Applying Benford’s Law to Detect Accounting Data Manipulation in the Banking Industry," Journal of Financial Services Research, Springer;Western Finance Association, vol. 59(1), pages 115-142, April.
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