Bibliographic coupling explained

Bibliographic coupling, like co-citation, is a similarity measure that uses citation analysis to establish a similarity relationship between documents. Bibliographic coupling occurs when two works reference a common third work in their bibliographies. It is an indication that a probability exists that the two works treat a related subject matter.[1]

Two documents are bibliographically coupled if they both cite one or more documents in common. The "coupling strength" of two given documents is higher the more citations to other documents they share. The figure to the right illustrates the concept of bibliographic coupling. In the figure, documents A and B both cite documents C, D and E. Thus, documents A and B have a bibliographic coupling strength of 3 - the number of elements in the intersection of their two reference lists.

Similarly, two authors are bibliographically coupled if the cumulative reference lists of their respective oeuvres each contain a reference to a common document, and their coupling strength also increases with the citations to other documents that their share. If the cumulative reference list of an author's oeuvre is determined as the multiset union of the documents that the author has co-authored, then the author bibliographic coupling strength of two authors (or more precisely, of their oeuvres) is defined as the size of the multiset intersection of their cumulative reference lists, however.[2]

Bibliographic coupling can be useful in a wide variety of fields, since it helps researchers find related research done in the past. On the other hand, two documents are co-cited if they are both independently cited by one or more documents.

History

The concept of bibliographic coupling was introduced by M. M. Kessler of MIT in a paper published in 1963,[3] and has been embraced in the work of the information scientist Eugene Garfield.[4] It is one of the earliest citation analysis methods for document similarity computation and some have questioned its usefulness, pointing out that two works may reference completely unrelated subject matter in the third. Furthermore, bibliographic coupling is a retrospective similarity measure,[5] meaning the information used to establish the similarity relationship between documents lies in the past and is static, i.e. bibliographic coupling strength cannot change over time, since outgoing citation counts are fixed.

The co-citation analysis approach introduced by Henry Small and published in 1973 addressed this shortcoming of bibliographic coupling by considering a document's incoming citations to assess similarity, a measure that can change over time. Additionally, the co-citation measure reflects the opinion of many authors and thus represents a better indicator of subject similarity.[6]

In 1972 Robert Amsler published a paper[7] describing a measure for determining subject similarity between two documents by fusing bibliographic coupling and co-citation analysis.[8]

In 1981 Howard White and Belver Griffith introduced author co-citation analysis (ACA).[9] Not until 2008 did Dangzhi Zhao and Andreas Strotmann combine their work and that of M. M. Kessler to define author bibliographic coupling analysis (ABCA), noting that as long as authors are active this metric is not static and that it is particularly useful when combined with ACA.[2]

More recently, in 2009, Gipp and Beel introduced a new approach termed Co-citation Proximity Analysis (CPA). CPA is based on the concept of co-citation, but represents a refinement to Small's measure in that CPA additionally considers the placement and proximity of citations within a document's full-text. The assumption is that citations in closer proximity are more likely to exhibit a stronger similarity relationship.[10]

In summary, a chronological overview of citation analysis methods includes:

Applications

Online sites that make use of bibliographic coupling includeThe Collection of Computer Science Bibliographies and CiteSeer.IST

See also

References

Bibliographic Coupling

Author Bibliographic Coupling

Co-citation analysis

Co-citation Proximity Analysis (CPA)

Author Co-citation Analysis (ACA)

Citation Studies in a More General Context

Further reading

For an interesting summary of the progression of the study of citations see.[11] The paper is more a memoir than a research paper, filled with decisions, research expectations, interests and motivations—including the story of how Henry Small approached Belver Griffith with the idea of co-citation and they became collaborators, mapping science as a whole.

External links

Notes and References

  1. Martyn . J . 1964 . Bibliographic coupling . Journal of Documentation . 20 . 4. 236 . 10.1108/eb026352.
  2. Zhao . D. . Strotmann . A. . 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 . 59 . 13. 2070–2086 . 10.1002/asi.20910 . free .
  3. "Bibliographic coupling between scientific papers," American Documentation 24 (1963), pp. 123-131.
  4. See for example "Multiple Independent Discovery and Creativity in Science," Current Contents, Nov. 3, 1980, pp. 5-10, reprinted in Essays of an Information Scientist, vol. 4 (1979-80), pp. 660-665.
  5. Garfield Eugene, 2001.From Bibliographic Coupling to Co-Citation Analysis via Algorithmic Historio-Bibliography presented at Drexel University, Philadelphia, PA
  6. 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 (JASIS), volume 24(4), pp. 265-269. doi = 10.1002/asi.4630240406
  7. Robert Amsler, Dec. 1972 "Applications of citation-based automatic classification", Linguistics Research Center, University Texas at Austin, Technical Report 72-14.
  8. http://webla.sourceforge.net/javadocs/pt/tumba/links/Amsler.html Class Amsler
  9. White . Howard D. . Griffith . Belver C. . 1981 . Author Cocitation: A Literature Measure of Intellectual Structure . Journal of the American Society for Information Science . 32 . 3. 163–171 . 10.1002/asi.4630320302 .
  10. Bela Gipp and Joeran Beel, 2009 Citation Proximity Analysis (CPA) – A new approach for identifying related work based on Co-Citation Analysis in Proceedings of the 12th international conference on scientometrics and informetrics (issi’09), Rio de Janeiro (Brazil), 2009, pp. 571-575.
  11. Small . Henry . 2001 . Belver and Henry . 10.1023/a:1019690918490 . Scientometrics . 51 . 3. 489–497 . 5962665 .
  12. Bela Gipp, Norman Meuschke & Mario Lipinski, 2015. "CITREC: An Evaluation Framework for Citation-Based Similarity Measures based on TREC Genomics and PubMed Central" in Proceedings of the iConference 2015, Newport Beach, California, 2015.