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Analysis of reference and citation copying in evolving bibliographic networks

Author

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  • Pandey, Pradumn Kumar
  • Singh, Mayank
  • Goyal, Pawan
  • Mukherjee, Animesh
  • Chakrabarti, Soumen

Abstract

Extensive literature demonstrates how the copying of references (links) can lead to the emergence of various structural properties (e.g., power-law degree distribution and bipartite cores) in bibliographic and other similar directed networks. However, it is also well known that the copying process is incapable of mimicking the number of directed triangles in such networks; neither does it have the power to explain the obsolescence of older papers. In this paper, we propose RefOrCite, a new model that allows for copying of both the references from (i.e., out-neighbors of) as well as the citations to (i.e., in-neighbors of) an existing node. In contrast, the standard copying model (CP) only copies references. While retaining its spirit, RefOrCite differs from the Forest Fire (FF) model in ways that makes RefOrCite amenable to mean-field analysis for degree distribution, triangle count, and densification. Empirically, RefOrCite gives the best overall agreement with observed degree distribution, triangle count, diameter, h-index, and the growth of citations to newer papers.

Suggested Citation

  • Pandey, Pradumn Kumar & Singh, Mayank & Goyal, Pawan & Mukherjee, Animesh & Chakrabarti, Soumen, 2020. "Analysis of reference and citation copying in evolving bibliographic networks," Journal of Informetrics, Elsevier, vol. 14(1).
    • Handle: RePEc:eee:infome:v:14:y:2020:i:1:s1751157719303384
    DOI: 10.1016/j.joi.2019.101003
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    References listed on IDEAS

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    1. Michal Brzezinski, 2015. "Power laws in citation distributions: evidence from Scopus," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 213-228, April.
    2. Zheng Xie & Zhenzheng Ouyang & Pengyuan Zhang & Dongyun Yi & Dexing Kong, 2015. "Modeling the Citation Network by Network Cosmology," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-13, March.
    3. Dorogovtsev, S. N. & Mendes, J.F.F., 2013. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780199686711.
    4. Wang, Mingyang & Yu, Guang & Yu, Daren, 2009. "Effect of the age of papers on the preferential attachment in citation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4273-4276.
    5. Michaël Charles Waumans & Hugues Bersini, 2016. "Genealogical Trees of Scientific Papers," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-15, March.
    6. Ren, Fu-Xin & Shen, Hua-Wei & Cheng, Xue-Qi, 2012. "Modeling the clustering in citation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3533-3539.
    7. Caldarelli, Guido, 2007. "Scale-Free Networks: Complex Webs in Nature and Technology," OUP Catalogue, Oxford University Press, number 9780199211517.
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