IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v76y2008i2d10.1007_s11192-007-1935-1.html
   My bibliography  Save this article

Bibliographic coupling, common abstract stems and clustering: A comparison of two document-document similarity approaches in the context of science mapping

Author

Listed:
  • Per Ahlgren

    (Swedish School of Library and Information Science)

  • Bo Jarneving

    (Swedish School of Library and Information Science)

Abstract

This paper deals with two document-document similarity approaches in the context of science mapping: bibliographic coupling and a text approach based on the number of common abstract stems. We used 43 articles, published in the journal Information Retrieval, as test articles. An information retrieval expert performed a classification of these articles. We used the cosine measure for normalization, and the complete linkage method was used for clustering the articles. A number of articles pairs were ranked (1) according to descending normalized coupling strength, and (2) according to descending normalized frequency of common abstract stems. The degree of agreement between the two obtained rankings was low, as measured by Kendall’s tau. The agreement between the two cluster solutions, one for each approach, was fairly low, according to the adjusted Rand index. However, there were examples of perfect agreement between the coupling solution and the stems solution. The classification generated by the expert contained larger groups compared to the coupling and stems solutions, and the agreement between the two solutions and the classification was not high. According to the adjusted Rand index, though, the stems solution was a better approximation of the classification than the coupling solution. With respect to cluster quality, the overall Silhouette value was slightly higher for the stems solution. Examples of homogeneous cluster structures, as well as negative Silhouette values, were found with regard to both solutions. The expert classification indicates that the field of information retrieval, as represented by one volume of articles published in Information Retrieval, is fairly heterogeneous regarding research themes, since the classification is associated with 15 themes. The complete linkage method, in combination with the upper tail rule, gave rise to a fairly good approximation of the classification with respect to the number of identified groups, especially in case of the stems approach.

Suggested Citation

  • Per Ahlgren & Bo Jarneving, 2008. "Bibliographic coupling, common abstract stems and clustering: A comparison of two document-document similarity approaches in the context of science mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(2), pages 273-290, August.
    • Handle: RePEc:spr:scient:v:76:y:2008:i:2:d:10.1007_s11192-007-1935-1
    DOI: 10.1007/s11192-007-1935-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-007-1935-1
    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/s11192-007-1935-1?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, 1965. "Comparison of the results of bibliographic coupling and analytic subject indexing," American Documentation, Wiley Blackwell, vol. 16(3), pages 223-233, July.
    2. H. P. F. Peters & R. R. Braam & A. F. J. van Raan, 1995. "Cognitive resemblance and citation relations in chemical engineering publications," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 46(1), pages 9-21, January.
    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. Ping Liu & Qiong Wu & Xiangming Mu & Kaipeng Yu & Yiting Guo, 2015. "Detecting the intellectual structure of library and information science based on formal concept analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 737-762, September.
    2. Yuen-Hsien Tseng & Ming-Yueh Tsay, 2013. "Journal clustering of library and information science for subfield delineation using the bibliometric analysis toolkit: CATAR," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 503-528, May.
    3. David N. Matzig & Clemens Schmid & Felix Riede, 2023. "Mapping the field of cultural evolutionary theory and methods in archaeology using bibliometric methods," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-17, December.
    4. Minh Nguyen Quang & Tim Rogers & Jan Hofman & Ana B Lanham, 2019. "New framework for automated article selection applied to a literature review of Enhanced Biological Phosphorus Removal," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-42, May.
    5. Vilker Zucolotto Pessin & Luciana Harue Yamane & Renato Ribeiro Siman, 2022. "Smart bibliometrics: an integrated method of science mapping and bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3695-3718, June.
    6. Nicolaisen, Jeppe & Frandsen, Tove Faber, 2012. "Consensus formation in science modeled by aggregated bibliographic coupling," Journal of Informetrics, Elsevier, vol. 6(2), pages 276-284.
    7. Xia Gao & Jiancheng Guan, 2009. "Networks of scientific journals: An exploration of Chinese patent data," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(1), pages 283-302, July.
    8. Cristian Colliander & Per Ahlgren, 2012. "Experimental comparison of first and second-order similarities in a scientometric context," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 675-685, February.
    9. Ahlgren, Per & Colliander, Cristian, 2009. "Document–document similarity approaches and science mapping: Experimental comparison of five approaches," Journal of Informetrics, Elsevier, vol. 3(1), pages 49-63.
    10. Yuen-Hsien Tseng & Chun-Yen Chang & M. Shane Tutwiler & Ming-Chao Lin & James P. Barufaldi, 2013. "A scientometric analysis of the effectiveness of Taiwan’s educational research projects," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 1141-1166, June.
    11. Sandra Boric & Edgar Schiebel & Christian Schlogl & Michaela Hildebrandt & Christina Hofer & Doris M. Macht, 2021. "Research in Autonomous Driving – A Historic Bibliometric View of the Research Development in Autonomous Driving," International Journal of Innovation and Economic Development, Inovatus Services Ltd., vol. 7(5), pages 27-44, December.

    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. Jarneving, Bo, 2007. "Bibliographic coupling and its application to research-front and other core documents," Journal of Informetrics, Elsevier, vol. 1(4), pages 287-307.
    2. Ahlgren, Per & Colliander, Cristian, 2009. "Document–document similarity approaches and science mapping: Experimental comparison of five approaches," Journal of Informetrics, Elsevier, vol. 3(1), pages 49-63.
    3. Jarneving, Bo, 2007. "Complete graphs and bibliographic coupling: A test of the applicability of bibliographic coupling for the identification of cognitive cores on the field level," Journal of Informetrics, Elsevier, vol. 1(4), pages 338-356.
    4. Yi-Ming Wei & Jin-Wei Wang & Tianqi Chen & Bi-Ying Yu & Hua Liao, 2018. "Frontiers of Low-Carbon Technologies: Results from Bibliographic Coupling with Sliding Window," CEEP-BIT Working Papers 116, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    5. van Eck, N.J.P. & Waltman, L., 2009. "How to Normalize Co-Occurrence Data? An Analysis of Some Well-Known Similarity Measures," ERIM Report Series Research in Management ERS-2009-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. van Raan, A. F. J. & van Leeuwen, Th. N., 2002. "Assessment of the scientific basis of interdisciplinary, applied research: Application of bibliometric methods in Nutrition and Food Research," Research Policy, Elsevier, vol. 31(4), pages 611-632, May.
    7. Sumita Raghuram & Philipp Tuertscher & Raghu Garud, 2010. "Research Note ---Mapping the Field of Virtual Work: A Cocitation Analysis," Information Systems Research, INFORMS, vol. 21(4), pages 983-999, December.
    8. Bo Jarneving, 2001. "The cognitive structure of current cardiovascular research," Scientometrics, Springer;Akadémiai Kiadó, vol. 50(3), pages 365-389, March.
    9. Chaoqun Ni & Cassidy R. Sugimoto & Blaise Cronin, 2013. "Visualizing and comparing four facets of scholarly communication: producers, artifacts, concepts, and gatekeepers," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1161-1173, March.
    10. P. Vinkler, 1999. "Ratio of short term and long term impact factors and similarities of chemistry journals represented by references," Scientometrics, Springer;Akadémiai Kiadó, vol. 46(3), pages 621-633, November.
    11. Lola García-Santiago & Felix Moya-Anegón, 2009. "Using co-outlinks to mine heterogeneous networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(3), pages 681-702, June.
    12. Howard D. White, 2001. "Author-centered bibliometrics through CAMEOs: Characterizations automatically made and edited online," Scientometrics, Springer;Akadémiai Kiadó, vol. 51(3), pages 607-637, July.
    13. Luis Felipe Cândido & Jose Carlos Lazaro & Adriano Olivier de Freitas e Silva & José de Paula Barros Neto, 2023. "Sustainability Transitions in the Construction Sector: A Bibliometric Review," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    14. Christian Sternitzke & Isumo Bergmann, 2009. "Similarity measures for document mapping: A comparative study on the level of an individual scientist," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(1), pages 113-130, January.
    15. Huang, Chen-Hao & Liu, John S. & Ho, Mei Hsiu-Ching & Chou, Tzu-Chuan, 2022. "Towards more convergent main paths: A relevance-based approach," Journal of Informetrics, Elsevier, vol. 16(3).
    16. Sjögårde, Peter & Ahlgren, Per, 2018. "Granularity of algorithmically constructed publication-level classifications of research publications: Identification of topics," Journal of Informetrics, Elsevier, vol. 12(1), pages 133-152.
    17. Dahesh, Mehran Badin & Tabarsa, Gholamali & Zandieh, Mostafa & Hamidizadeh, Mohammadreza, 2020. "Reviewing the intellectual structure and evolution of the innovation systems approach: A social network analysis," Technology in Society, Elsevier, vol. 63(C).
    18. Ali Gazni & Fereshteh Didegah, 2016. "The relationship between authors’ bibliographic coupling and citation exchange: analyzing disciplinary differences," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 609-626, May.
    19. García-Lillo, Francisco & Seva-Larrosa, Pedro & Sánchez-García, Eduardo, 2023. "What is going on in entrepreneurship research? A bibliometric and SNA analysis," Journal of Business Research, Elsevier, vol. 158(C).
    20. Sitaram Devarakonda & Dmitriy Korobskiy & Tandy Warnow & George Chacko, 2020. "Viewing computer science through citation analysis: Salton and Bergmark Redux," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 271-287, October.

    More about this item

    Statistics

    Access and download statistics

    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:76:y:2008:i:2:d:10.1007_s11192-007-1935-1. 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.