IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v122y2020i2d10.1007_s11192-019-03303-9.html
   My bibliography  Save this article

Related records retrieval and pennant retrieval: an exploratory case study

Author

Listed:
  • Müge Akbulut

    (Ankara Yıldırım Beyazıt University)

  • Yaşar Tonta

    (Hacettepe University)

  • Howard D. White

    (Drexel University)

Abstract

The Related Records feature in the Web of Science retrieves records that share at least one item in their reference lists with the references of a seed record. This search method, known as bibliographic coupling, does not always yield topically relevant results. Our exploratory case study asks: How do retrievals of the type used in pennant diagrams compare with retrievals through Related Records? Pennants are two-dimensional visualizations of documents co-cited with a seed paper. In them, the well-known tf*idf (term frequency*inverse document frequency) formula is used to weight the co-citation counts. The weights have psychological interpretations from relevance theory; given the seed, tf predicts a co-cited document’s cognitive effects on the user, and idf predicts the user’s relative ease in relating its title to the seed’s title. We chose two seed papers from information science, one with only two references and the other with 20, and used them to retrieve 50 documents per method in WoS for each of our two seeds. We illustrate with pennant diagrams. Pennant retrieval indeed produced more relevant documents, especially for the paper with only two references, and it produced mostly different ones. Related Records performed almost as well on the paper with the longer reference list, improving remarkably as the coupling units between the seed and other papers increased. We argue that relevance rankings based on co-citation, with pennant-style weighting as an option, would be a desirable addition to WoS and similar databases.

Suggested Citation

  • Müge Akbulut & Yaşar Tonta & Howard D. White, 2020. "Related records retrieval and pennant retrieval: an exploratory case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 957-987, February.
  • Handle: RePEc:spr:scient:v:122:y:2020:i:2:d:10.1007_s11192-019-03303-9
    DOI: 10.1007/s11192-019-03303-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-019-03303-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-019-03303-9?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. Giovanni Colavizza & Kevin W. Boyack & Nees Jan van Eck & Ludo Waltman, 2018. "The Closer the Better: Similarity of Publication Pairs at Different Cocitation Levels," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(4), pages 600-609, April.
    2. Howard D. White, 2007. "Combining bibliometrics, information retrieval, and relevance theory, Part 2: Some implications for information science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(4), pages 583-605, February.
    3. 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.
    4. Julie Bichteler & Edward A. Eaton, 1980. "The combined use of bibliographic coupling and cocitation for document retrieval," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 31(4), pages 278-282, August.
    5. M. E. Maron, 1977. "On indexing, retrieval and the meaning of about," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 28(1), pages 38-43, January.
    6. S. E. Robertson & K. Sparck Jones, 1976. "Relevance weighting of search terms," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 27(3), pages 129-146, May.
    7. Y. Y. Yao, 1995. "Measuring retrieval effectiveness based on user preference of documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 46(2), pages 133-145, March.
    8. Shen, Si & Zhu, Danhao & Rousseau, Ronald & Su, Xinning & Wang, Dongbo, 2019. "A refined method for computing bibliographic coupling strengths," Journal of Informetrics, Elsevier, vol. 13(2), pages 605-615.
    9. Howard D. White, 2010. "Some new tests of relevance theory in information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 653-667, June.
    10. Howard D. White, 2015. "Co-cited author retrieval and relevance theory: examples from the humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2275-2299, March.
    11. Howard D. White, 2018. "Pennants for Garfield: bibliometrics and document retrieval," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 757-778, February.
    12. Charles H. Smith & Patrick Georges & Ngoc Nguyen, 2015. "Statistical tests for ‘related records’ search results," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1665-1677, December.
    13. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    14. Christopher W. Belter, 2017. "A relevance ranking method for citation-based search results," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(2), pages 731-746, August.
    15. Howard D. White, 2007. "Combining bibliometrics, information retrieval, and relevance theory, Part 1: First examples of a synthesis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(4), pages 536-559, February.
    16. Masaki Eto, 2013. "Evaluations of context-based co-citation searching," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(2), pages 651-673, February.
    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. Daniel Fonseca Costa & Brenda Melissa Fonseca & Lélis Pedro Andrade & Bruno César Melo Moreira, 2023. "Bibliometric and scientometric analysis of the scientific field in taxation," SN Business & Economics, Springer, vol. 3(1), pages 1-28, January.

    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. Masaki Eto, 2013. "Evaluations of context-based co-citation searching," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(2), pages 651-673, February.
    2. Jensen, Scott & Liu, Xiaozhong & Yu, Yingying & Milojevic, Staša, 2016. "Generation of topic evolution trees from heterogeneous bibliographic networks," Journal of Informetrics, Elsevier, vol. 10(2), pages 606-621.
    3. 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).
    4. Yun, Jinhyuk, 2022. "Generalization of bibliographic coupling and co-citation using the node split network," Journal of Informetrics, Elsevier, vol. 16(2).
    5. 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.
    6. Maryam Yaghtin & Hajar Sotudeh & Mahdieh Mirzabeigi & Seyed Mostafa Fakhrahmad & Mehdi Mohammadi, 2019. "In quest of new document relations: evaluating co-opinion relations between co-citations and its impact on Information retrieval effectiveness," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 987-1008, May.
    7. Nassiri, Isar & Masoudi-Nejad, Ali & Jalili, Mahdi & Moeini, Ali, 2013. "Normalized Similarity Index: An adjusted index to prioritize article citations," Journal of Informetrics, Elsevier, vol. 7(1), pages 91-98.
    8. Yadav, Pratyush & Pervin, Nargis, 2022. "Towards efficient navigation in digital libraries: Leveraging popularity, semantics and communities to recommend scholarly articles," Journal of Informetrics, Elsevier, vol. 16(4).
    9. Piñeiro-Chousa, Juan & López-Cabarcos, M. Ángeles & Romero-Castro, Noelia María & Pérez-Pico, Ada María, 2020. "Innovation, entrepreneurship and knowledge in the business scientific field: Mapping the research front," Journal of Business Research, Elsevier, vol. 115(C), pages 475-485.
    10. Guan-Can Yang & Gang Li & Chun-Ya Li & Yun-Hua Zhao & Jing Zhang & Tong Liu & Dar-Zen Chen & Mu-Hsuan Huang, 2015. "Using the comprehensive patent citation network (CPC) to evaluate patent value," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1319-1346, December.
    11. Rey-Long Liu, 2017. "A new bibliographic coupling measure with descriptive capability," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 915-935, February.
    12. Lilian Cervo Cabrera & Carlos Eduardo Caldarelli & Marcia Regina Gabardo Camara, 2020. "Mapping collaboration in international coffee certification research," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2597-2618, September.
    13. 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.
    14. Chris W. Belter, 2013. "A bibliometric analysis of NOAA’s Office of Ocean Exploration and Research," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 629-644, May.
    15. Ding, Ying, 2011. "Community detection: Topological vs. topical," Journal of Informetrics, Elsevier, vol. 5(4), pages 498-514.
    16. Ignacio Rodríguez-Rodríguez & José-Víctor Rodríguez & Niloofar Shirvanizadeh & Andrés Ortiz & Domingo-Javier Pardo-Quiles, 2021. "Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining," IJERPH, MDPI, vol. 18(16), pages 1-29, August.
    17. Ooms, Tahnee & Klaser, Klaudijo & Ishkanian, Armine, 2023. "The role of academia practice partnerships in the well-being economy: Retracing synergies between health and social sciences using bibliometric analysis," Health Policy, Elsevier, vol. 138(C).
    18. Manta Eduard Mihai & Davidescu Adriana Ana Maria & Geambasu Maria Cristina & Florescu Margareta Stela, 2023. "Exploring the research area of direct taxation. An empirical analysis based on bibliometric analysis results," Management & Marketing, Sciendo, vol. 18(s1), pages 355-383, December.
    19. Leslier Valenzuela-Fernández & Manuel Escobar-Farfán, 2022. "Zero-Waste Management and Sustainable Consumption: A Comprehensive Bibliometric Mapping Analysis," Sustainability, MDPI, vol. 14(23), pages 1-24, December.
    20. 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.

    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:spr:scient:v:122:y:2020:i:2:d:10.1007_s11192-019-03303-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.