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Frequency of occurrence of numbers in the World Wide Web

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  • Dorogovtsev, S.N.
  • Mendes, J.F.F.
  • Oliveira, J.G.

Abstract

The distribution of numbers in human documents is determined by a variety of diverse natural and human factors, whose relative significance can be evaluated by studying the numbers’ frequency of occurrence. Although it has been studied since the 1880's, this subject remains poorly understood. Here, we obtain the detailed statistics of numbers in the World Wide Web, finding that their distribution is a heavy-tailed dependence which splits in a set of power-law ones. In particular, we find that the frequency of numbers associated to western calendar years shows an uneven behavior: 2004 represents a ‘singular critical’ point, appearing with a strikingly high frequency; as we move away from it, the decreasing frequency allows us to compare the amounts of existing information on the past and on the future. Moreover, while powers of ten occur extremely often, allowing us to obtain statistics up to the huge 10127, ‘non-round’ numbers occur in a much more limited range, the variations of their frequencies being dramatically different from standard statistical fluctuations. These findings provide a view of the array of numbers used by humans as a highly non-equilibrium and inhomogeneous system, and shed a new light on an issue that, once fully investigated, could lead to a better understanding of many sociological and psychological phenomena.

Suggested Citation

  • Dorogovtsev, S.N. & Mendes, J.F.F. & Oliveira, J.G., 2006. "Frequency of occurrence of numbers in the World Wide Web," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 548-556.
  • Handle: RePEc:eee:phsmap:v:360:y:2006:i:2:p:548-556
    DOI: 10.1016/j.physa.2005.06.064
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    References listed on IDEAS

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    1. 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.
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    3. Réka Albert & Hawoong Jeong & Albert-László Barabási, 1999. "Diameter of the World-Wide Web," Nature, Nature, vol. 401(6749), pages 130-131, September.
    4. Bernardo A. Huberman & Lada A. Adamic, 1999. "Growth dynamics of the World-Wide Web," Nature, Nature, vol. 401(6749), pages 131-131, September.
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    Cited by:

    1. M. Jayasree & C. S. Pavana Jyothi & P. Ramya, 2018. "Benford’s Law and Stock Market—The Implications for Investors: The Evidence from India Nifty Fifty," Jindal Journal of Business Research, , vol. 7(2), pages 103-121, December.
    2. Jovani, Roger & Fortuna, Miguel A., 2007. "The shape of the past in the World Wide Web: Scale-free patterns and dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 683-688.
    3. Ausloos, M. & Herteliu, C. & Ileanu, B., 2015. "Breakdown of Benford’s law for birth data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 736-745.
    4. Gao-Feng Gu & Xiong Xiong & Fei Ren & Wei-Xing Zhou & Wei Zhang, 2011. "The position profiles of order cancellations in an emerging stock market," Papers 1112.6085, arXiv.org, revised May 2013.
    5. Clippe, Paulette & Ausloos, Marcel, 2012. "Benford’s law and Theil transform of financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6556-6567.
    6. Mir, T.A., 2012. "The law of the leading digits and the world religions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 792-798.
    7. 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).
    8. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical shape function of limit-order books in the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5182-5188.
    9. Mandeep K. Dhami & Ian K. Belton & Elizabeth Merrall & Andrew McGrath & Sheila M. Bird, 2020. "Criminal Sentencing by Preferred Numbers," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 17(1), pages 139-163, March.

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