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Evaluating journal impact based on weighted citations

Author

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  • Fuli Zhang

    (Anshan Normal University)

Abstract

Publishing at high-rank journals is a common objective to most researchers, and there’s a crucial need for a journal ranking system with universal recognition. This paper presents a quantitative approach to rank scientific journals. The approach, HR-PageRank, combines weighted PageRank according to author’s H-index, and relevance between citing and cited papers. The output of the proposed approach is compared against journal impact factor, H5-index, PageRank algorithm and China Computer Federation ranking list. The experiments of quantifying scholarly impact objectively are conducted in two real scholarly data sets: (1) Microsoft Academic Graph and (2) Digital Bibliography and Library Project. Our experimental results indicate that HR-PageRank algorithm outperforms the well-known PageRank algorithm in finding the influential journals according to Spearman’s rank correlation coefficient, discounted cumulated gain and the correlation C.

Suggested Citation

  • Fuli Zhang, 2017. "Evaluating journal impact based on weighted citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 1155-1169, November.
    • Handle: RePEc:spr:scient:v:113:y:2017:i:2:d:10.1007_s11192-017-2510-z
    DOI: 10.1007/s11192-017-2510-z
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    8. Xie, Qing & Zhang, Xinyuan & Song, Min, 2021. "A network embedding-based scholar assessment indicator considering four facets: Research topic, author credit allocation, field-normalized journal impact, and published time," Journal of Informetrics, Elsevier, vol. 15(4).
    9. Zhang, Baolong & Wang, Hao & Deng, Sanhong & Su, Xinning, 2020. "Measurement and analysis of Chinese journal discriminative capacity," Journal of Informetrics, Elsevier, vol. 14(1).

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