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Benford’s law and first letter of words

Author

Listed:
  • Yan, Xiaoyong
  • Yang, Seong-Gyu
  • Kim, Beom Jun
  • Minnhagen, Petter

Abstract

A universal First-Letter Law (FLL) is derived and described. It predicts the percentages of first letters for words in novels. The FLL is akin to Benford’s law (BL) of first digits, which predicts the percentages of first digits in a data collection of numbers. Both are universal in the sense that FLL only depends on the numbers of letters in the alphabet, whereas BL only depends on the number of digits in the base of the number system. The existence of these types of universal laws appears counter-intuitive. Nonetheless both describe data very well. Relations to some earlier works are given. FLL predicts that an English author on the average starts about 16 out of 100 words with the English letter ‘t’. This is corroborated by data, yet an author can freely write anything. Fuller implications and the applicability of FLL remain for the future.

Suggested Citation

  • Yan, Xiaoyong & Yang, Seong-Gyu & Kim, Beom Jun & Minnhagen, Petter, 2018. "Benford’s law and first letter of words," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 305-315.
    • Handle: RePEc:eee:phsmap:v:512:y:2018:i:c:p:305-315
    DOI: 10.1016/j.physa.2018.08.133
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    References listed on IDEAS

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    1. Fewster, R. M., 2009. "A Simple Explanation of Benford's Law," The American Statistician, American Statistical Association, vol. 63(1), pages 26-32.
    2. Pietronero, L. & Tosatti, E. & Tosatti, V. & Vespignani, A., 2001. "Explaining the uneven distribution of numbers in nature: the laws of Benford and Zipf," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 293(1), pages 297-304.
    3. Yan, Xiaoyong & Minnhagen, Petter & Jensen, Henrik Jeldtoft, 2016. "The likely determines the unlikely," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 112-119.
    4. Yan, Xiaoyong & Minnhagen, Petter, 2016. "Randomness versus specifics for word-frequency distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 828-837.
    5. Yan, Xiaoyong & Minnhagen, Petter, 2018. "The dependence of frequency distributions on multiple meanings of words, codes and signs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 554-564.
    6. Xiaoyong Yan & Petter Minnhagen, 2015. "Maximum Entropy, Word-Frequency, Chinese Characters, and Multiple Meanings," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-19, May.
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    Cited by:

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    4. Lee, Kang-Bok & Han, Sumin & Jeong, Yeasung, 2020. "COVID-19, flattening the curve, and Benford’s law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).

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