IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v15y2021i3s1751157721000390.html
   My bibliography  Save this article

Scoring the resourcefulness of researchers using bibliographic coupling patterns

Author

Listed:
  • Prathap, Gangan
  • Ujum, Ephrance Abu
  • Kumar, Sameer
  • Ratnavelu, Kuru

Abstract

Networks constructed from citation and publication data can be mined to find top-ranking authors or papers using graph-theoretic algorithms. This article proposes an indicator called the “follow-score” that identifies which authors are the most resourceful to “follow” in terms of referencing patterns within a given body of literature. For testing purposes, we use Web of Science indexed publications under the subject category of “Information Science & Library Science” between the years 2008 and 2018 inclusive. Using the top-ranking follow-worthy authors, we search the study dataset for other similar researchers using cosine similarity.

Suggested Citation

  • Prathap, Gangan & Ujum, Ephrance Abu & Kumar, Sameer & Ratnavelu, Kuru, 2021. "Scoring the resourcefulness of researchers using bibliographic coupling patterns," Journal of Informetrics, Elsevier, vol. 15(3).
    • Handle: RePEc:eee:infome:v:15:y:2021:i:3:s1751157721000390
    DOI: 10.1016/j.joi.2021.101168
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157721000390
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2021.101168?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    2. Bouyssou, Denis & Marchant, Thierry, 2016. "Ranking authors using fractional counting of citations: An axiomatic approach," Journal of Informetrics, Elsevier, vol. 10(1), pages 183-199.
    3. Vladimir Batagelj, 2020. "On fractional approach to analysis of linked networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 621-633, May.
    4. Loet Leydesdorff & Caroline S. Wagner & Lutz Bornmann, 2018. "Betweenness and diversity in journal citation networks as measures of interdisciplinarity—A tribute to Eugene Garfield," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 567-592, February.
    5. S. Redner, 1998. "How popular is your paper? An empirical study of the citation distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 4(2), pages 131-134, July.
    6. Ying Ding & Erjia Yan & Arthur Frazho & James Caverlee, 2009. "PageRank for ranking authors in co‐citation networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(11), pages 2229-2243, November.
    7. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    8. Ma, Ruimin, 2012. "Author bibliographic coupling analysis: A test based on a Chinese academic database," Journal of Informetrics, Elsevier, vol. 6(4), pages 532-542.
    9. Mike Thelwall & Kayvan Kousha, 2014. "Academia.edu: Social network or Academic Network?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 721-731, April.
    10. Dangzhi Zhao & Andreas Strotmann, 2014. "The knowledge base and research front of information science 2006–2010: An author cocitation and bibliographic coupling analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(5), pages 995-1006, May.
    11. Blaise Cronin & Debora Shaw, 2002. "Identity-creators and image-makers: Using citation analysis and thick description to put authors in their place," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(1), pages 31-49, April.
    12. Gangan Prathap & Somenath Mukherjee, 2020. "Letter to the Editor: Comments on the paper of Batagelj—on fractional approach to analysis of linked networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2717-2722, September.
    13. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    14. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    15. Dangzhi Zhao & Andreas Strotmann, 2008. "Evolution of research activities and intellectual influences in information science 1996–2005: Introducing author bibliographic‐coupling analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(13), pages 2070-2086, November.
    16. Chen, Chaomei & Chen, Yue & Horowitz, Mark & Hou, Haiyan & Liu, Zeyuan & Pellegrino, Donald, 2009. "Towards an explanatory and computational theory of scientific discovery," Journal of Informetrics, Elsevier, vol. 3(3), pages 191-209.
    17. Howard D. White & Belver C. Griffith, 1981. "Author cocitation: A literature measure of intellectual structure," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 32(3), pages 163-171, May.
    18. Bu, Yi & Ni, Shaokang & Huang, Win-bin, 2017. "Combining multiple scholarly relationships with author cocitation analysis: A preliminary exploration on improving knowledge domain mappings," Journal of Informetrics, Elsevier, vol. 11(3), pages 810-822.
    19. Jeong, Yoo Kyung & Song, Min & Ding, Ying, 2014. "Content-based author co-citation analysis," Journal of Informetrics, Elsevier, vol. 8(1), pages 197-211.
    20. A. O. Zhirov & O. V. Zhirov & D. L. Shepelyansky, 2010. "Two-dimensional ranking of Wikipedia articles," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(4), pages 523-531, October.
    21. He, Bing & Ding, Ying & Yan, Erjia, 2012. "Mining patterns of author orders in scientific publications," Journal of Informetrics, Elsevier, vol. 6(3), pages 359-367.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hur, Wonchang, 2024. "Entropy, heterogeneity, and their impact on technology progress," Journal of Informetrics, Elsevier, vol. 18(2).
    2. Wu, Yingwen & Ji, Yangjian, 2023. "Identifying firm-specific technology opportunities from the perspective of competitors by using association rule mining," Journal of Informetrics, Elsevier, vol. 17(2).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Song Yanhui & Wu Lijuan & Qiu Junping, 2021. "A comparative study of first and all-author bibliographic coupling analysis based on Scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1125-1147, February.
    2. Yun, Jinhyuk & Ahn, Sejung & Lee, June Young, 2020. "Return to basics: Clustering of scientific literature using structural information," Journal of Informetrics, Elsevier, vol. 14(4).
    3. Pin Li & Guoli Yang & Chuanqi Wang, 2019. "Visual topical analysis of library and information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1753-1791, December.
    4. Yu-Wei Chang & Mu-Hsuan Huang & Chiao-Wen Lin, 2015. "Evolution of research subjects in library and information science based on keyword, bibliographical coupling, and co-citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2071-2087, December.
    5. Yang, Siluo & Han, Ruizhen & Wolfram, Dietmar & Zhao, Yuehua, 2016. "Visualizing the intellectual structure of information science (2006–2015): Introducing author keyword coupling analysis," Journal of Informetrics, Elsevier, vol. 10(1), pages 132-150.
    6. Jun-Ping Qiu & Ke Dong & Hou-Qiang Yu, 2014. "Comparative study on structure and correlation among author co-occurrence networks in bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1345-1360, November.
    7. Yang, Siluo & Wang, Feifei, 2015. "Visualizing information science: Author direct citation analysis in China and around the world," Journal of Informetrics, Elsevier, vol. 9(1), pages 208-225.
    8. Yong Huang & Yi Bu & Ying Ding & Wei Lu, 2018. "Number versus structure: towards citing cascades," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 2177-2193, December.
    9. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
    10. Ying Huang & Wolfgang Glänzel & Lin Zhang, 2021. "Tracing the development of mapping knowledge domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6201-6224, July.
    11. Liu, Yunmei & Yang, Liu & Chen, Min, 2021. "A new citation concept: Triangular citation in the literature," Journal of Informetrics, Elsevier, vol. 15(2).
    12. Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    13. Mingchun Cao & Ilan Alon, 2020. "Intellectual Structure of the Belt and Road Initiative Research: A Scientometric Analysis and Suggestions for a Future Research Agenda," Sustainability, MDPI, vol. 12(17), pages 1-40, August.
    14. Tsung-Ming Hsiao & Kuang-hua Chen, 2020. "The dynamics of research subfields for library and information science: an investigation based on word bibliographic coupling," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 717-737, October.
    15. Fan, Yangliu & Lehmann, Sune & Blok, Anders, 2022. "Extracting the interdisciplinary specialty structures in social media data-based research: A clustering-based network approach," Journal of Informetrics, Elsevier, vol. 16(3).
    16. Ruhao Zhang & Junpeng Yuan, 2022. "Enhanced author bibliographic coupling analysis using semantic and syntactic citation information," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7681-7706, December.
    17. Aparisi Torrijo, Sofia & Ribes Giner, Gabriela, 2022. "Entrepreneurial leadership factors: a bibliometric analysis for the 2000-2020 period," Cuadernos de Gestión, Universidad del País Vasco - Instituto de Economía Aplicada a la Empresa (IEAE).
    18. Jochen Gläser & Wolfgang Glänzel & Andrea Scharnhorst, 2017. "Same data—different results? Towards a comparative approach to the identification of thematic structures in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 981-998, May.
    19. Marco Galvagno, 2017. "Bibliometric literature review: An opportunity for marketing scholars," MERCATI & COMPETITIVIT?, FrancoAngeli Editore, vol. 2017(4), pages 7-15.
    20. Bu, Yi & Ni, Shaokang & Huang, Win-bin, 2017. "Combining multiple scholarly relationships with author cocitation analysis: A preliminary exploration on improving knowledge domain mappings," Journal of Informetrics, Elsevier, vol. 11(3), pages 810-822.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:infome:v:15:y:2021:i:3:s1751157721000390. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.