Evaluating journal impact based on weighted citations

Fuli Zhang ()
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Fuli Zhang: Anshan Normal University

Scientometrics, 2017, vol. 113, issue 2, No 25, 1155-1169

Abstract: 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.

Keywords: Scholarly big data; Journal impact; H-index (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (10)

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DOI: 10.1007/s11192-017-2510-z

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