IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v128y2023i6d10.1007_s11192-023-04704-7.html
   My bibliography  Save this article

Time-stamp based network evolution model for citation networks

Author

Listed:
  • Monachary Kammari

    (University of Hyderabad)

  • Durga Bhavani S

    (University of Hyderabad)

Abstract

Citation score has become a very important metric to assess the quality of a publication in the current global ranking scenario. In this context, the study of citation networks gains importance as it helps in understanding the citation process as well as in analyzing citation trends in the research world. Citation networks are modeled as directed acyclic graphs in which publications of the authors are considered as nodes and citations between the papers form the links. In this paper, we propose an additive Time-Stamp based Network Evolution(TNE) model for citation networks, extending Price’s preferential attachment model by including the recency effect on the citation process without neglecting the impact of classical papers. We propose a more meaningful definition of clustering coefficient for citation networks in terms of ’citation triangles’. Further, the network simulated by the TNE model with best-fit parameters is compared with the real-world(DBLP) citation network. The results of various significance tests show that the simulated network matches very well with the DBLP citation network in terms of several network properties.

Suggested Citation

  • Monachary Kammari & Durga Bhavani S, 2023. "Time-stamp based network evolution model for citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3723-3741, June.
    • Handle: RePEc:spr:scient:v:128:y:2023:i:6:d:10.1007_s11192-023-04704-7
    DOI: 10.1007/s11192-023-04704-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-023-04704-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-023-04704-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. S. R. Goldberg & H. Anthony & T. S. Evans, 2015. "Modelling citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1577-1604, December.
    2. 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.
    3. Heather Keathley-Herring & Eileen Van Aken & Fernando Gonzalez-Aleu & Fernando Deschamps & Geert Letens & Pablo Cardenas Orlandini, 2016. "Assessing the maturity of a research area: bibliometric review and proposed framework," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 927-951, November.
    4. Timur Narbaev & Diana Amirbekova, 2021. "Research Productivity in Emerging Economies: Empirical Evidence from Kazakhstan," Publications, MDPI, vol. 9(4), pages 1-19, November.
    5. Dennys Eduardo Rossetto & Roberto Carlos Bernardes & Felipe Mendes Borini & Cristiane Chaves Gattaz, 2018. "Structure and evolution of innovation research in the last 60 years: review and future trends in the field of business through the citations and co-citations analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1329-1363, June.
    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. Pi, Xiaochen & Tang, Longkun & Chen, Xiangzhong, 2021. "A directed weighted scale-free network model with an adaptive evolution mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    8. Mingers, John & Leydesdorff, Loet, 2015. "A review of theory and practice in scientometrics," European Journal of Operational Research, Elsevier, vol. 246(1), pages 1-19.
    9. Ren, Zhuo-Ming, 2019. "Age preference of metrics for identifying significant nodes in growing citation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 325-332.
    10. Hajra, Kamalika Basu & Sen, Parongama, 2006. "Modelling aging characteristics in citation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 368(2), pages 575-582.
    11. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wei Cheng & Dejun Zheng & Shaoxiong Fu & Jingfeng Cui, 2024. "Closer in time and higher correlation: disclosing the relationship between citation similarity and citation interval," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4495-4512, July.
    2. Zhaoping Yan & Kaiyu Fan, 2024. "An integrated indicator for evaluating scientific papers: considering academic impact and novelty," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 6909-6929, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wu, Yan & Fu, Tom Z.J. & Chiu, Dah Ming, 2014. "Generalized preferential attachment considering aging," Journal of Informetrics, Elsevier, vol. 8(3), pages 650-658.
    2. Xu, Shuqi & Mariani, Manuel Sebastian & Lü, Linyuan & Medo, Matúš, 2020. "Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data," Journal of Informetrics, Elsevier, vol. 14(1).
    3. Xiaorui Jiang & Xiaoping Sun & Hai Zhuge, 2013. "Graph-based algorithms for ranking researchers: not all swans are white!," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 743-759, September.
    4. Timur Narbaev & Diana Amirbekova, 2021. "Research Productivity in Emerging Economies: Empirical Evidence from Kazakhstan," Publications, MDPI, vol. 9(4), pages 1-19, November.
    5. S. R. Goldberg & H. Anthony & T. S. Evans, 2015. "Modelling citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1577-1604, December.
    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. 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).
    8. Lutz Bornmann & Robin Haunschild & Sven E. Hug, 2018. "Visualizing the context of citations referencing papers published by Eugene Garfield: a new type of keyword co-occurrence analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 427-437, February.
    9. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    10. Yanzhu Hu & Huiyang Zhao & Xinbo Ai, 2016. "Inferring Weighted Directed Association Network from Multivariate Time Series with a Synthetic Method of Partial Symbolic Transfer Entropy Spectrum and Granger Causality," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-25, November.
    11. Gallego-Losada, María-Jesús & Montero-Navarro, Antonio & García-Abajo, Elisa & Gallego-Losada, Rocío, 2023. "Digital financial inclusion. Visualizing the academic literature," Research in International Business and Finance, Elsevier, vol. 64(C).
    12. Manuel Sánchez-Pérez & Nuria Rueda-López & María Belén Marín-Carrillo & Eduardo Terán-Yépez, 2021. "Theoretical dilemmas, conceptual review and perspectives disclosure of the sharing economy: a qualitative analysis," Review of Managerial Science, Springer, vol. 15(7), pages 1849-1883, October.
    13. Mohadab, Mohamed El & Bouikhalene, Belaid & Safi, Said, 2020. "Bibliometric method for mapping the state of the art of scientific production in Covid-19," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    14. Matthias Aistleitner & Jakob Kapeller & Stefan Steinerberger, 2018. "Citation Patterns in Economics and Beyond," Working Papers Series 85, Institute for New Economic Thinking.
    15. Ghousia Jabeen & Gurunadham Goli & Kafila & R. Gobinath, 2024. "A bibliometric review on gender equity in human resource management," Future Business Journal, Springer, vol. 10(1), pages 1-18, December.
    16. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Costa, 2023. "Correlating article citedness and journal impact: an empirical investigation by field on a large-scale dataset," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1877-1894, March.
    17. Muhammad Ashraf Fauzi, 2023. "Social media in disaster management: review of the literature and future trends through bibliometric analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(2), pages 953-975, September.
    18. Bouckenooghe, Dave & Schwarz, Gavin M. & Kanar, Adam & Sanders, Karin, 2021. "Revisiting research on attitudes toward organizational change: Bibliometric analysis and content facet analysis," Journal of Business Research, Elsevier, vol. 135(C), pages 137-148.
    19. Magdalena Mucowska, 2021. "Trends of Environmentally Sustainable Solutions of Urban Last-Mile Deliveries on the E-Commerce Market—A Literature Review," Sustainability, MDPI, vol. 13(11), pages 1-26, May.
    20. Sergio Copiello, 2019. "Research Interest: another undisclosed (and redundant) algorithm by ResearchGate," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 351-360, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:128:y:2023:i:6:d:10.1007_s11192-023-04704-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.