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Time-stamp based network evolution model for citation networks

Author

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  • 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
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    References listed on IDEAS

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    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.

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