Abstract
The power-law distribution and the Garfield’s Law of Concentration of journal citation have long been verified by empirical data. As a relatively new type of reference, the URL references are cited more and more frequently in the scientific papers and their distribution is proved to fit for the Garfield’s Law of Concentration too. In this article, we collect three URL references datasets extracted from papers written by researchers belonging to three big research groups : Chinese Academy of Sciences, Max Planck Institute, and the whole Chinese scientific researchers. Through the curve-fitting with SPSS and contrast the results with the judgment standard of power-law distribution, we verify that there also exists power-law distribution in the citation frequency of hostnames in these three URL references datasets. And our experimental results show that the range of power exponent in the journal references and the URL references are different. Started from the concrete empirical procedures and the final experimental results, we analyze four factors that may lead to this difference between journal references and URL references: the sample size, the sampling method, the concentration of citation and the type property of citation.
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References
Egghe, L. (2005). Power laws in the information production process: Lotkaian informetrics. Amsterdam: Elsevier.
Egghe, L., & Rousseau, R. (2006). An informetric model for the Hirsch-index. Scientometrics, 69(1), 121–129.
Fang, A. L., Gao, Q. S., & Zhang, S. Y. (2007). A study on the test of power-law distribution of citation network. Statistics and Decision, 14, 22–24 (In Chinese).
Garfield, E. (1972). Citation analysis as a tool in journal evaluation. Science, 178(4060), 471–479.
Hu, H. B., & Wang, L. (2005). A brief history of power law distributions. Physics, 34(12), 889–896. (In Chinese).
Krashakov, S. A., Teslyuk, A. B., & Shchur, L. N. (2006). On the universality of rank distributions of website popularity. Computer Networks, 50(11), 1769–1780.
Larivière, V., Gingras, Y., & Archambault, É. (2009). The decline in the concentration of citation, 1900–2007. Journal of the American Society for Information Science and Technology, 60(4), 858–862.
Li, Y. J., & Chen, Y. S. (2009). Survey analysis on the web citations of the periodicals on library science. Sci-Tech Information Development & Economy, 19(6), 43–47 (In Chinese).
Liu, C. H. (2004). Evaluation of medical information resources on the Internet by citation analysis: A primary study. Chin J Med Libr Inf Sci, 13(6), 58–60 (In Chinese).
Liu, Z. M., An, M. R., & Zhang, C. Y. (2005). Web citation’s author analysis. Information Science, 23(2), 202–204. (In Chinese).
Liu, Y. X., Rao, I. K. R., & Rousseau, R. (2009). Empirical series of journal h-indices: The JCR category Horticulture as a case study. Scientometrics, 80(1), 59–74.
Meng, L. S. (1982). Chinese Science Citation Analysis. Master’s thesis, Library of Chinese Academy of Sciences, Beijing (In Chinese).
Pan, N. (2006). An analysis of author of web citation from the core information science periodicals. Journal of Academic Library and Information Science, 24(6), 86–89. (In Chinese).
Price, D. J. de Solla (1965). Networks of science paper. Science, 149(3683), 510–515.
Price, D. J. de Solla (1976). A general theory of bibliometric and other cumulative advantage processes. Journal of the American Society for Information Science, 27(5–6), 292–306.
Redner, S. (1998). How popular is your paper? An empirical study of the citation distribution. European Physical Journal B, 4, 131–134.
W3C (1994). Uniform Resource Locators. http://www.w3.org/Addressing/rfc1738.txt. Accessed 4 Jan. 2011.
Wang, L. (2008). Research on the distribution of the citations of social science-the statistical analysis of the 2005 JCR social science. Library Development, 8, 104–107. (In Chinese).
Wren, J. D. (2004). 404 not found: the stability and persistence of URLs published in MEDLINE. Bioinformatics, 20(5), 668–672.
Yang, S. L., Ma, F., Song, Y. H., & Qiu, J. P. (2010a). A longitudinal analysis of citation distribution breadth for Chinese scholars. Scientometrics, 85, 755–765.
Yang, S. L., Qiu, J. P., & Xiong, Z. Y. (2010b). An empirical study on the utilization of web academic resources in humanities and social sciences based on web citations. Scientometrics, 84, 1–19.
Ye, F. Y., & Rousseau, R. (2008). The power law model and total career h-index sequences. Journal of Informetrics, 2, 288–297.
Ye, F. Y., & Rousseau, R. (2010). Probing the h-core: An investigation of the tail-core ratio for rank distributions. Scientometrics, 84, 431–439.
Zhang, C. Y., An, M. R., Wang, J. F., & Jiang, R. Z. (2004). Quantitative exploration of web citation. Journal of the China Society for Scientific and Technical Information, 23(5), 566–570 (In Chinese).
Acknowledgments
I would particularly thank Xiaomin Liu for providing the CSCD URL references data used for this study. I thank the reviewers and editors for their useful comments to this article.
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Lin, F. A study on power-law distribution of hostnames in the URL references. Scientometrics 88, 191–198 (2011). https://doi.org/10.1007/s11192-011-0377-y
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DOI: https://doi.org/10.1007/s11192-011-0377-y