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  <doc>
    <id>8966</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>101379</pageFirst>
    <pageLast/>
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    <volume>17</volume>
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    <title language="eng">Article’s scientific prestige: Measuring the impact of individual articles in the web of science</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Journal of Informetrics</parentTitle>
    <identifier type="doi">10.1016/j.joi.2023.101379</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">07.01.2023</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-86380</enrichment>
    <author>Ying Chen</author>
    <submitter>Janina Zittel</submitter>
    <author>Thorsten Koch</author>
    <author>Nazgul Zakiyeva</author>
    <author>Kailiang Liu</author>
    <author>Zhitong Xu</author>
    <author>Chun-houh Chen</author>
    <author>Junji Nakano</author>
    <author>Keisuke Honda</author>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="persons" number="zakiyeva">Zakiyeva, Nazgul</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>8638</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>101379</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>17</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Article's Scientific Prestige: Measuring the Impact of Individual Articles in the Web of Science</title>
    <abstract language="eng">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&#13;
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&#13;
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&#13;
reflect the scientific impact of individual articles. The number of references and coauthors are&#13;
less relevant to scientific impact, but subjects do make a difference.</abstract>
    <identifier type="urn">urn:nbn:de:0297-zib-86380</identifier>
    <identifier type="doi">https://doi.org/10.1016/j.joi.2023.101379</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">07.01.2023</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-86380</enrichment>
    <author>Ying Chen</author>
    <submitter>Nazgul Zakiyeva</submitter>
    <author>Thorsten Koch</author>
    <author>Nazgul Zakiyeva</author>
    <author>Kailiang Liu</author>
    <author>Zhitong Xu</author>
    <author>Chun-houh Chen</author>
    <author>Junji Nakano</author>
    <author>Keisuke Honda</author>
    <series>
      <title>ZIB-Report</title>
      <number>22-07</number>
    </series>
    <collection role="persons" number="koch">Koch, Thorsten</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aim">Applied Algorithmic Intelligence Methods</collection>
    <collection role="projects" number="MODAL-EnergyLab">MODAL-EnergyLab</collection>
    <collection role="persons" number="zakiyeva">Zakiyeva, Nazgul</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/8638/ASP_ZIB_report_2023.pdf</file>
  </doc>
</export-example>
