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Identifying 'seed' papers in sciences

Author

Listed:
  • Jean J. Wang

    (Nanjing University
    Jiangsu Key Laboratory of Data Engineering and Knowledge Service
    Nanjing University–University of Illinois)

  • Sarah X. Shao

    (Nanjing University
    Jiangsu Key Laboratory of Data Engineering and Knowledge Service
    Nanjing University–University of Illinois)

  • Fred Y. Ye

    (Nanjing University
    Jiangsu Key Laboratory of Data Engineering and Knowledge Service
    Nanjing University–University of Illinois)

Abstract

A concise quantitative method is established for identifying ‘seed’ papers in sciences. The method is set up following h-type metrics based on co-citation network analysis. With defining original-seed (O-Seed) and dominant-seed (D-Seed) by measurable h-strength and second-order h-type degree centrality, O-seed resembles to be a ‘root’ and D-seed develops to become ‘stem’. Using dataset from Web of Science (WoS), the ‘seed’ papers in research fields of graphene, genome editing, and h-set studies are identified. Graphene D-Seed paper and genome editing D-Seed paper are representative outputs of the 2010 Nobel Prize in Physics and the 2020 Nobel Prize in Chemistry respectively. H-set O-Seed and D-Seed are the same paper that first proposed the concept of h-index. The ‘seed’ papers are characterized by not only high citations, but also network structure and core function in sciences.

Suggested Citation

  • Jean J. Wang & Sarah X. Shao & Fred Y. Ye, 2021. "Identifying 'seed' papers in sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6001-6011, July.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:7:d:10.1007_s11192-021-03980-5
    DOI: 10.1007/s11192-021-03980-5
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    References listed on IDEAS

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