Article's Scientific Prestige: measuring the impact of individual articles in the Web of Science

39 Pages Posted: 24 Mar 2022

See all articles by Ying Chen

Ying Chen

National University of Singapore (NUS) - Department of Mathematics

Thorsten Koch

Technische Universitat Berlin - Software and Algorithms for Discrete Optimization

Nazgul Zakiyeva

Zuse Institute Berlin

Kailiang Liu

affiliation not provided to SSRN

Zhitong Xu

National University of Singapore (NUS) - Department of Statistics and Applied Probability

Chun-houh Chen

Academia Sinica - Institute of Statistical Science

Junji Nakano

Chuo University

Keisuke Honda

The Institute of Statistical Mathematics

Date Written: February 17, 2022

Abstract

We performed a citation analysis on the Web of Science publications consisting of more than 63 million articles and 1.45 billion citations on 254 subjects from 1981 to 2020. We proposed the Article’s Scientific Prestige (ASP) metric and compared this metric to number of citations (#Cit) and journal grade in measuring the scientific impact of individual articles in the large-scale hierarchical and multi-disciplined citation network. In contrast to #Cit, ASP, that is computed based on the eigenvector centrality, considers both direct and indirect citations, and provides steady-state evaluation cross different disciplines. We found that ASP and #Cit are not aligned for most articles, with a growing mismatch amongst the less cited articles. While both metrics are reliable for evaluating the prestige of articles such as Nobel Prize winning articles, ASP tends to provide more persuasive rankings than #Cit when the articles are not highly cited. The journal grade, that is eventually determined by a few highly cited articles, is unable to properly reflect the scientific impact of individual articles. The number of references and coauthors are less relevant to scientific impact, but subjects do make a difference.

Keywords: citation network analysis, direct citations, scientific impact, eigenvector centrality, citations counts, cross-subject citations

Suggested Citation

Chen, Ying and Koch, Thorsten and Zakiyeva, Nazgul and Liu, Kailiang and Xu, Zhitong and Chen, Chun-houh and Nakano, Junji and Honda, Keisuke, Article's Scientific Prestige: measuring the impact of individual articles in the Web of Science (February 17, 2022). Available at SSRN: https://ssrn.com/abstract=4037131 or http://dx.doi.org/10.2139/ssrn.4037131

Ying Chen

National University of Singapore (NUS) - Department of Mathematics ( email )

119076
Singapore

Thorsten Koch (Contact Author)

Technische Universitat Berlin - Software and Algorithms for Discrete Optimization ( email )

Berlin
Germany

Nazgul Zakiyeva

Zuse Institute Berlin ( email )

Takustr. 7, 14195 Berlin
Berlin, DE 14195
Germany

Kailiang Liu

affiliation not provided to SSRN

Zhitong Xu

National University of Singapore (NUS) - Department of Statistics and Applied Probability

Block S16, Level 7,
6 Science Drive 2
Singapore, 117546

Chun-houh Chen

Academia Sinica - Institute of Statistical Science ( email )

Nankang
Taipei, 11529
Taiwan

Junji Nakano

Chuo University ( email )

2nd floor Blg 4 Tampa Campus
742-1 Higashinakano, Hachioji
Tokyo 192-03
Japan

Keisuke Honda

The Institute of Statistical Mathematics ( email )

4-6-7 Minami-Azabu
Minato-ku, Tokyo 106
Japan

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