Citation analysis

Citation analysis is the examination of the frequency, patterns, and graphs of citations in documents. It uses the pattern of citations, links from one document to another document, to reveal properties of the documents. A typical aim would be to identify the most important documents in a collection. A classic example is that of the citations between academic articles and books.[1][2] The judgements produced by judges of law to support their decisions refer back to judgements made in earlier cases so citation analysis in a legal context is important. Another example is provided by patents which contain prior art, citation earlier patents relevant to the current claim.

Documents can be associated with many other features in addition to citations, such as authors, publishers, journals as well as their actual texts. The general analysis of collections of documents is known as bibliometrics and citation analysis is a key part of that field. For example, bibliographic coupling and co-citation are association measures based on citation analysis (shared citations or shared references). The citations in a collection of documents can also be represented in forms such as a citation graph, as pointed out by Derek J. de Solla Price in his 1965 article "Networks of Scientific Papers".[3] This means that citation analysis draws on aspects of social network analysis and network science.

An early example of automated citation indexing was CiteSeer, which was used for citations between academic papers, while Google Scholar is an example of a modern system which includes more than just academic books and articles reflecting a wider range of information sources. Today, automated citation indexing[4] has changed the nature of citation analysis research, allowing millions of citations to be analyzed for large-scale patterns and knowledge discovery. Citation analysis tools can be used to compute various impact measures for scholars based on data from citation indices.[5][6][7] These have various applications, from the identification of expert referees to review papers and grant proposals, to providing transparent data in support of academic merit review, tenure, and promotion decisions. This competition for limited resources may lead to ethical questionable behavior to increase citations.[8][9]

A great deal of criticism has been made of the practice of naively using citation analyses to compare the impact of different scholarly articles without taking into account other factors which may affect citation patterns.[10] Among these criticisms, a recurrent one focuses on “field-dependent factors”, which refers to the fact that citation practices vary from one area of science to another, and even between fields of research within a discipline.[11]


While citation indexes were originally designed for information retrieval, they are increasingly used for bibliometrics and other studies involving research evaluation. Citation data is also the basis of the popular journal impact factor.

There is a large body of literature on citation analysis, sometimes called scientometrics, a term invented by Vasily Nalimov, or more specifically bibliometrics. The field blossomed with the advent of the Science Citation Index, which now covers source literature from 1900 on. The leading journals of the field are Scientometrics, Informetrics, and the Journal of the American Society of Information Science and Technology. ASIST also hosts an electronic mailing list called SIGMETRICS at ASIST.[12] This method is undergoing a resurgence based on the wide dissemination of the Web of Science and Scopus subscription databases in many universities, and the universally available free citation tools such as CiteBase, CiteSeerX, Google Scholar, and the former Windows Live Academic (now available with extra features as Microsoft Academic Search). Methods of citation analysis research include qualitative, quantitative and computational approaches. The main foci of such scientometric studies have included productivity comparisons, institutional research rankings, journal rankings [13] establishing faculty productivity and tenure standards,[14] assessing the influence of top scholarly articles,[15] and developing profiles of top authors and institutions in terms of research performance [16]

Legal citation analysis is a citation analysis technique for analyzing legal documents to facilitate the understanding of the inter-related regulatory compliance documents by the exploration the citations that connect provisions to other provisions within the same document or between different documents. Legal citation analysis uses a citation graph extracted from a regulatory document, which could supplement E-discovery - a process that leverages on technological innovations in big data analytics.[17][18][19][20]


In a 1965 paper, Derek J. de Solla Price described the inherent linking characteristic of the SCI as "Networks of Scientific Papers".[3] The links between citing and cited papers became dynamic when the SCI began to be published online. The Social Sciences Citation Index became one of the first databases to be mounted on the Dialog system[21] in 1972. With the advent of the CD-ROM edition, linking became even easier and enabled the use of bibliographic coupling for finding related records. In 1973, Henry Small published his classic work on Co-Citation analysis which became a self-organizing classification system that led to document clustering experiments and eventually an "Atlas of Science" later called "Research Reviews".

The inherent topological and graphical nature of the worldwide citation network which is an inherent property of the scientific literature was described by Ralph Garner (Drexel University) in 1965.[22]

The use of citation counts to rank journals was a technique used in the early part of the nineteenth century but the systematic ongoing measurement of these counts for scientific journals was initiated by Eugene Garfield at the Institute for Scientific Information who also pioneered the use of these counts to rank authors and papers. In a landmark paper of 1965 he and Irving Sher showed the correlation between citation frequency and eminence in demonstrating that Nobel Prize winners published five times the average number of papers while their work was cited 30 to 50 times the average. In a long series of essays on the Nobel and other prizes Garfield reported this phenomenon. The usual summary measure is known as impact factor, the number of citations to a journal for the previous two years, divided by the number of articles published in those years. It is widely used, both for appropriate and inappropriate purposes—in particular, the use of this measure alone for ranking authors and papers is therefore quite controversial.

In an early study in 1964 of the use of Citation Analysis in writing the history of DNA, Garfield and Sher demonstrated the potential for generating historiographs, topological maps of the most important steps in the history of scientific topics. This work was later automated by E. Garfield, A. I. Pudovkin of the Institute of Marine Biology, Russian Academy of Sciences and V. S. Istomin of Center for Teaching, Learning, and Technology, Washington State University and led to the creation of the HistCite [23] software around 2002.

Automatic citation indexing was introduced in 1998 by Lee Giles, Steve Lawrence and Kurt Bollacker [24] and enabled automatic algorithmic extraction and grouping of citations for any digital academic and scientific document. Where previous citation extraction was a manual process, citation measures could now scale up and be computed for any scholarly and scientific field and document venue, not just those selected by organizations such as ISI. This led to the creation of new systems for public and automated citation indexing, the first being CiteSeer (now CiteSeerX, soon followed by Cora, which focused primarily on the field of computer science and information science. These were later followed by large scale academic domain citation systems such as the Google Scholar and Microsoft Academic. Such autonomous citation indexing is not yet perfect in citation extraction or citation clustering with an error rate estimated by some at 10% though a careful statistical sampling has yet to be done. This has resulted in such authors as Ann Arbor, Milton Keynes, and Walton Hall being credited with extensive academic output.[25] SCI claims to create automatic citation indexing through purely programmatic methods. Even the older records have a similar magnitude of error.

Citation analysis for legal documents

Citation analysis for legal documents is an approach to facilitate the understanding and analysis of inter-related regulatory compliance documents by exploration of the citations that connect provisions to other provisions within the same document or between different documents. Citation analysis uses a citation graph extracted from a regulatory document, which could supplement E-discovery - a process that leverages on technological innovations in big data analytics.[19][20][26]


E-publishing. Due to the unprecedented growth of electronic resource (e-resource) availability, one of the questions currently being explored is, "how often are e-resources being cited in my field?"[27] For instance, there are claims that on-line access to computer science literature leads to higher citation rates,[28] however, humanities articles may suffer if not in print.

Self-citations. It has been criticized that authors game the system by accumulating citations by citing themselves excessively. For instance, it has been found that men tend to cite themselves more often than women. However, this may be caused by the fact that men have been over-represented in science for most of history and in most fields and are therefore in a position of higher power and thus productivity.[29]

See also

Methods of citation analysis for document similarity computation


  1. Rubin, Richard (2010). Foundations of library and information science (3rd ed.). New York: Neal-Schuman Publishers. ISBN 978-1-55570-690-6.
  2. Garfield, E. Citation Indexing - Its Theory and Application in Science, Technology and Humanities Philadelphia:ISI Press, 1983.
  3. 1 2 Derek J. de Solla Price (July 30, 1965). "Networks of Scientific Papers" (PDF). Science. 149 (3683): 510515. doi:10.1126/science.149.3683.510. PMID 14325149.
  4. Giles, C. Lee; Bollacker, Kurt D.; Lawrence, Steve (1998), "CiteSeer: an automatic citation indexing system.", Digital libraries 98 : the Third ACM Conference on Digital Libraries, June 23–26, 1998, Pittsburgh, PA, New York: Association for Computing Machinery: 89–98, doi:10.1145/276675.276685, ISBN 0-89791-965-3, retrieved July 7, 2011
  5. Examples include subscription-based tools based on proprietary data, such as Web of Science and Scopus, and free tools based on open data, such as Scholarometer by Filippo Menczer and his team.
  6. Kaur, Jasleen; Diep Thi Hoang; Xiaoling Sun; Lino Possamai; Mohsen JafariAsbagh; Snehal Patil; Filippo Menczer (2012). "Scholarometer: A Social Framework for Analyzing Impact across Disciplines". PLOS ONE. 7 (9): e43235. doi:10.1371/journal.pone.0043235.
  7. Hoang, D.; Kaur, J.; Menczer, F. (2010), "Crowdsourcing Scholarly Data", Proceedings of the WebSci10: Extending the Frontiers of Society On-Line, April 26-27th, 2010, Raleigh, NC: US
  8. Anderson, M.S. van; Ronning, E.A. van; de Vries, R.; Martison, B.C. (2007). "The perverse effects of competition on scientists' work and relationship". Science and Engineering Ethics. 4 (13): 437–461. doi:10.1007/s11948-007-9042-5.
  9. Wesel, M. van (2016). "Evaluation by Citation: Trends in Publication Behavior, Evaluation Criteria, and the Strive for High Impact Publications". Science and Engineering Ethics. 22 (1): 199–225. doi:10.1007/s11948-015-9638-0.
  10. Bornmann, L.; Daniel, H. D. (2008). "What do citation counts measure? A review of studies on citing behavior". Journal of Documentation. 64 (1): 45–80. doi:10.1108/00220410810844150.
  11. Anauati, Maria Victoria and Galiani, Sebastian and Gálvez, Ramiro H., Quantifying the Life Cycle of Scholarly Articles Across Fields of Economic Research (November 11, 2014). Available at SSRN:
  12. "The American Society for Information Science & Technology". The Information Society for the Information Age. Retrieved 2006-05-21.
  13. Lowry, Paul Benjamin; Moody, Gregory D.; Gaskin, James; Galletta, Dennis F.; Humpherys, Sean; Barlow, Jordan B.; and Wilson, David W. (2013). "Evaluating journal quality and the Association for Information Systems (AIS) Senior Scholars’ journal basket via bibliometric measures: Do expert journal assessments add value?," MIS Quarterly (MISQ), vol. 37(4), 993–1012. Also, see YouTube video narrative of this paper at:
  14. Dean, Douglas L; Lowry, Paul Benjamin; and Humpherys, Sean (2011). "Profiling the research productivity of tenured information systems faculty at U.S. institutions," MIS Quarterly (MISQ), vol. 35(1), pp. 1–15 (ISSN 0276-7783).
  15. Karuga, Gilbert G.; Lowry, Paul Benjamin; and Richardson, Vernon J. (2007). "Assessing the impact of premier information systems research over time," Communications of the Association for Information Systems, vol. 19(7), pp. 115–131 (
  16. Lowry, Paul Benjamin; Karuga, Gilbert G.; and Richardson, Vernon J. (2007). "Assessing leading institutions, faculty, and articles in premier information systems research journals," Communications of the Association for Information Systems, vol. 20(16), pp. 142–203 (
  17. Retrieved November 29, 2009. Missing or empty |title= (help)
  18. Mohammad Hamdaqa and A. Hamou-Lhadj, "Citation Analysis: An Approach for Facilitating the Understanding and the Analysis of Regulatory Compliance Documents", In Proc. of the 6th International Conference on Information Technology, Las Vegas, USA
  19. 1 2 "E-Discovery Special Report: The Rising Tide of Nonlinear Review". Hudson Global. Archived from the original on 3 July 2012. Retrieved 1 July 2012. by Cat Casey and Alejandra Perez
  20. 1 2 "What Technology-Assisted Electronic Discovery Teaches Us About The Role Of Humans In Technology - Re-Humanizing Technology-Assisted Review". Forbes. Retrieved 1 July 2012.
  21. "Dialog, A Thomson Business". "Dialog invented online information services". Retrieved 2006-05-21.
  23. Eugene Garfield; A. I. Pudovkin; V. S. Istomin (2002). "Algorithmic Citation-Linked Historiography—Mapping the Literature of Science". Presented the ASIS&T 2002: Information, Connections and Community. 65th Annual Meeting of ASIST in Philadelphia, PA. November 18–21, 2002. Retrieved 2006-05-21.
  24. C.L. Giles, K. Bollacker, S. Lawrence, "CiteSeer: An Automatic Citation Indexing System," DL'98 Digital Libraries, 3rd ACM Conference on Digital Libraries, pp. 89-98, 1998.
  25. Postellon DC (March 2008). "Hall and Keynes join Arbor in the citation indexes". Nature. 452 (7185): 282. doi:10.1038/452282b. PMID 18354457.
  26. Hamdaqa, M.; A Hamou-Lhadj (2009). Citation Analysis: An Approach for Facilitating the Understanding and the Analysis of Regulatory Compliance Documents. Las Vegas, NV: IEEE. pp. 278–283. doi:10.1109/ITNG.2009.161. ISBN 978-1-4244-3770-2.
  27. Zhao, Lisa. "How Librarian Used E-Resources--An Analysis of Citations in CCQ." Cataloging & Classification Quarterly 42(1) (2006): 117-131.
  28. Lawrence, Steve. Free online availability substantially increases a paper's impact. Nature volume 411 (number 6837) (2001): 521. Also online at
  29. Singh Chawla, Dalmeet (5 July 2016). "Men cite themselves more than women do". Nature. Nature. Retrieved 7 July 2016.
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