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Large-scale structure of time evolving citation networks

Author

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  • E. A. Leicht
  • G. Clarkson
  • K. Shedden
  • M. E.J. Newman

Abstract

In this paper we examine a number of methods for probing and understanding the large-scale structure of networks that evolve over time. We focus in particular on citation networks, networks of references between documents such as papers, patents, or court cases. We describe three different methods of analysis, one based on an expectation-maximization algorithm, one based on modularity optimization, and one based on eigenvector centrality. Using the network of citations between opinions of the United States Supreme Court as an example, we demonstrate how each of these methods can reveal significant structural divisions in the network and how, ultimately, the combination of all three can help us develop a coherent overall picture of the network's shape. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2007

Suggested Citation

  • E. A. Leicht & G. Clarkson & K. Shedden & M. E.J. Newman, 2007. "Large-scale structure of time evolving citation networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 59(1), pages 75-83, September.
    • Handle: RePEc:spr:eurphb:v:59:y:2007:i:1:p:75-83
    DOI: 10.1140/epjb/e2007-00271-7
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    Citations

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    Cited by:

    1. Gao, Lei & Li, Ruiqi & Shu, Panpan & Wang, Wei & Gao, Hui & Cai, Shimin, 2018. "Effects of individual popularity on information spreading in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 32-39.
    2. Diego R. Amancio & Osvaldo N. Oliveira jr & Luciano F. Costa, 2015. "Topological-collaborative approach for disambiguating authors’ names in collaborative networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 465-485, January.
    3. Selen Onel & Abe Zeid & Sagar Kamarthi, 2011. "The structure and analysis of nanotechnology co-author and citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 119-138, October.
    4. Huang, Ying & Li, Ruinan & Zou, Fang & Jiang, Lidan & Porter, Alan L. & Zhang, Lin, 2022. "Technology life cycle analysis: From the dynamic perspective of patent citation networks," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    5. Kavitha Karunan & Hiran H. Lathabai & Thara Prabhakaran, 2017. "Discovering interdisciplinary interactions between two research fields using citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 335-367, October.
    6. Bommarito, Michael J. & Katz, Daniel Martin & Zelner, Jonathan L. & Fowler, James H., 2010. "Distance measures for dynamic citation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(19), pages 4201-4208.
    7. Andreas Spitz & Emőke-Ágnes Horvát, 2014. "Measuring Long-Term Impact Based on Network Centrality: Unraveling Cinematic Citations," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-12, October.
    8. Piccardi, Carlo & Calatroni, Lisa & Bertoni, Fabio, 2010. "Communities in Italian corporate networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5247-5258.
    9. Fabbri, Renato & Fabbri, Ricardo & Antunes, Deborah Christina & Pisani, Marilia Mello & de Oliveira, Osvaldo Novais, 2017. "Temporal stability in human interaction networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 92-105.
    10. Silva, Filipi N. & Amancio, Diego R. & Bardosova, Maria & Costa, Luciano da F. & Oliveira, Osvaldo N., 2016. "Using network science and text analytics to produce surveys in a scientific topic," Journal of Informetrics, Elsevier, vol. 10(2), pages 487-502.
    11. Atieh Mirshahvalad & Johan Lindholm & Mattias Derlén & Martin Rosvall, 2012. "Significant Communities in Large Sparse Networks," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-7, March.
    12. Sheridan, Paul & Yagahara, Yuichi & Shimodaira, Hidetoshi, 2012. "Measuring preferential attachment in growing networks with missing-timelines using Markov chain Monte Carlo," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 5031-5040.
    13. Wu, Ke & Liu, Xueming, 2021. "Community detection in directed acyclic graphs of adversary interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    14. József Popp & Péter Balogh & Judit Oláh & Sebastian Kot & Mónika Harangi Rákos & Péter Lengyel, 2018. "Social Network Analysis of Scientific Articles Published by Food Policy," Sustainability, MDPI, vol. 10(3), pages 1-20, February.
    15. Feng Hu & Lin Ma & Xiu-Xiu Zhan & Yinzuo Zhou & Chuang Liu & Haixing Zhao & Zi-Ke Zhang, 2021. "The aging effect in evolving scientific citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4297-4309, May.

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