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Power law distributions in information science: Making the case for logarithmic binning

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  • Staša Milojević

Abstract

We suggest partial logarithmic binning as the method of choice for uncovering the nature of many distributions encountered in information science (IS). Logarithmic binning retrieves information and trends “not visible” in noisy power law tails. We also argue that obtaining the exponent from logarithmically binned data using a simple least square method is in some cases warranted in addition to methods such as the maximum likelihood. We also show why often‐used cumulative distributions can make it difficult to distinguish noise from genuine features and to obtain an accurate power law exponent of the underlying distribution. The treatment is nontechnical, aimed at IS researchers with little or no background in mathematics.

Suggested Citation

  • Staša Milojević, 2010. "Power law distributions in information science: Making the case for logarithmic binning," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2417-2425, December.
    • Handle: RePEc:bla:jamist:v:61:y:2010:i:12:p:2417-2425
    DOI: 10.1002/asi.21426
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    Cited by:

    1. Necmi Gürsakal & Sadullah Çelik & Serkan Özdemir, 2023. "High-frequency words have higher frequencies in Turkish social sciences article," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1865-1887, April.
    2. Sahasranaman, Anand & Bettencourt, Luís M.A., 2021. "Life between the city and the village: Scaling analysis of service access in Indian urban slums," World Development, Elsevier, vol. 142(C).
    3. Chen, Li & Zheng, Linjiang & Xia, Li & Liu, Weining & Sun, Dihua, 2021. "Detecting and analyzing unlicensed taxis: A case study of Chongqing City," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    4. Hao-Ran Liu & Wei-Xing Zhou, 2023. "Visibility graph analysis of the grains and oilseeds indices," Papers 2304.05760, arXiv.org.

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