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PageRank variants in the evaluation of citation networks

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  • Nykl, Michal
  • Ježek, Karel
  • Fiala, Dalibor
  • Dostal, Martin

Abstract

This paper explores a possible approach to a research evaluation, by calculating the renown of authors of scientific papers. The evaluation is based on the citation analysis and its results should be close to a human viewpoint. The PageRank algorithm and its modifications were used for the evaluation of various types of citation networks. Our main research question was whether better evaluation results were based directly on an author network or on a publication network. Other issues concerned, for example, the determination of weights in the author network and the distribution of publication scores among their authors. The citation networks were extracted from the computer science domain in the ISI Web of Science database. The influence of self-citations was also explored. To find the best network for a research evaluation, the outputs of PageRank were compared with lists of prestigious awards in computer science such as the Turing and Codd award, ISI Highly Cited and ACM Fellows. Our experiments proved that the best ranking of authors was obtained by using a publication citation network from which self-citations were eliminated, and by distributing the same proportional parts of the publications’ values to their authors. The ranking can be used as a criterion for the financial support of research teams, for identifying leaders of such teams, etc.

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  • Nykl, Michal & Ježek, Karel & Fiala, Dalibor & Dostal, Martin, 2014. "PageRank variants in the evaluation of citation networks," Journal of Informetrics, Elsevier, vol. 8(3), pages 683-692.
    • Handle: RePEc:eee:infome:v:8:y:2014:i:3:p:683-692
    DOI: 10.1016/j.joi.2014.06.005
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    References listed on IDEAS

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    1. Erjia Yan & Ying Ding, 2012. "Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(7), pages 1313-1326, July.
    2. Erjia Yan & Ying Ding, 2012. "Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(7), pages 1313-1326, July.
    3. Ying Ding, 2011. "Applying weighted PageRank to author citation networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(2), pages 236-245, February.
    4. Dalibor Fiala, 2011. "Mining citation information from CiteSeer data," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(3), pages 553-562, March.
    5. Fiala, Dalibor, 2012. "Time-aware PageRank for bibliographic networks," Journal of Informetrics, Elsevier, vol. 6(3), pages 370-388.
    6. Lili Lin & Zhuoming Xu & Ying Ding & Xiaozhong Liu, 2013. "Finding topic-level experts in scholarly networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 797-819, December.
    7. Ying Ding, 2011. "Applying weighted PageRank to author citation networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(2), pages 236-245, February.
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    Cited by:

    1. Antonia Gogoglou & Antonis Sidiropoulos & Dimitrios Katsaros & Yannis Manolopoulos, 2017. "The fractal dimension of a citation curve: quantifying an individual’s scientific output using the geometry of the entire curve," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1751-1774, June.
    2. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2018. "How to evaluate rankings of academic entities using test data," Journal of Informetrics, Elsevier, vol. 12(3), pages 631-655.
    3. Yanan Wang & An Zeng & Ying Fan & Zengru Di, 2019. "Ranking scientific publications considering the aging characteristics of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 155-166, July.
    4. Shunshun Shi & Wenyu Zhang & Shuai Zhang & Jie Chen, 2018. "Does prestige dimension influence the interdisciplinary performance of scientific entities in knowledge flow? Evidence from the e-government field," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 1237-1264, November.
    5. Jun Zhang & Zhaolong Ning & Xiaomei Bai & Xiangjie Kong & Jinmeng Zhou & Feng Xia, 2017. "Exploring time factors in measuring the scientific impact of scholars," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1301-1321, September.
    6. Mariani, Manuel Sebastian & Medo, Matúš & Zhang, Yi-Cheng, 2016. "Identification of milestone papers through time-balanced network centrality," Journal of Informetrics, Elsevier, vol. 10(4), pages 1207-1223.
    7. Dejian Yu & Wanru Wang & Shuai Zhang & Wenyu Zhang & Rongyu Liu, 2017. "A multiple-link, mutually reinforced journal-ranking model to measure the prestige of journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 521-542, April.
    8. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2018. "Author ranking evaluation at scale," Journal of Informetrics, Elsevier, vol. 12(3), pages 679-702.
    9. Wang, Ruby W. & Wei, Shelia X. & Ye, Fred Y., 2021. "Extracting a core structure from heterogeneous information network using h-subnet and meta-path strength," Journal of Informetrics, Elsevier, vol. 15(3).
    10. Nykl, Michal & Campr, Michal & Ježek, Karel, 2015. "Author ranking based on personalized PageRank," Journal of Informetrics, Elsevier, vol. 9(4), pages 777-799.
    11. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2019. "Globalised vs averaged: Bias and ranking performance on the author level," Journal of Informetrics, Elsevier, vol. 13(1), pages 299-313.
    12. Ruijie Wang & Yuhao Zhou & An Zeng, 2023. "Evaluating scientists by citation and disruption of their representative works," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1689-1710, March.
    13. Fiala, Dalibor & Šubelj, Lovro & Žitnik, Slavko & Bajec, Marko, 2015. "Do PageRank-based author rankings outperform simple citation counts?," Journal of Informetrics, Elsevier, vol. 9(2), pages 334-348.
    14. Dunaiski, Marcel & Visser, Willem & Geldenhuys, Jaco, 2016. "Evaluating paper and author ranking algorithms using impact and contribution awards," Journal of Informetrics, Elsevier, vol. 10(2), pages 392-407.
    15. Dinesh Pradhan & Partha Sarathi Paul & Umesh Maheswari & Subrata Nandi & Tanmoy Chakraborty, 2017. "$$C^3$$ C 3 -index: a PageRank based multi-faceted metric for authors’ performance measurement," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 253-273, January.
    16. Jun Zhang & Yan Hu & Zhaolong Ning & Amr Tolba & Elsayed Elashkar & Feng Xia, 2018. "AIRank: Author Impact Ranking through Positions in Collaboration Networks," Complexity, Hindawi, vol. 2018, pages 1-16, June.
    17. Tortosa, Leandro & Vicent, Jose F. & Yeghikyan, Gevorg, 2021. "An algorithm for ranking the nodes of multiplex networks with data based on the PageRank concept," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    18. Massucci, Francesco Alessandro & Docampo, Domingo, 2019. "Measuring the academic reputation through citation networks via PageRank," Journal of Informetrics, Elsevier, vol. 13(1), pages 185-201.
    19. Jianlin Zhou & An Zeng & Ying Fan & Zengru Di, 2016. "Ranking scientific publications with similarity-preferential mechanism," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 805-816, February.
    20. Liwei Cai & Jiahao Tian & Jiaying Liu & Xiaomei Bai & Ivan Lee & Xiangjie Kong & Feng Xia, 2019. "Scholarly impact assessment: a survey of citation weighting solutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 453-478, February.
    21. Yu, Dejian & Sheng, Libo, 2021. "Influence difference main path analysis: Evidence from DNA and blockchain domain citation networks," Journal of Informetrics, Elsevier, vol. 15(4).

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