Citation analysis

Citation analysis is the examination of the frequency, patterns, and graphs of citations in articles and books.[1][2] It uses citations in scholarly works to establish links to other works or other researchers.[3] Citation analysis is one of the most widely used methods of bibliometrics. For example, bibliographic coupling and co-citation are association measures based on citation analysis (shared citations or shared references).

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. The first example of automated citation indexing was CiteSeer, later to be followed by Google Scholar.

Today citation analysis tools are easily available 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]

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.[12][13][14]

Issues raised by electronic 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?"[15] For instance, there are claims that on-line access to computer science literature leads to higher citation rates,[16] however, humanities articles may suffer if not in print.

See also

Methods of citation analysis for document similarity computation

Notes

  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. "Dimension of Citation Analysis". Retrieved 1 July 2012. by Loet Leydesdorff and Olga Amsterdamska
  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. and 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 (2015). "Evaluation by Citation: Trends in Publication Behavior, Evaluation Criteria, and the Strive for High Impact Publications". Science and Engineering Ethics. 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.
  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: http://ssrn.com/abstract=2523078
  12. 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.
  13. "E-Discovery Special Report: The Rising Tide of Nonlinear Review". Hudson Global. Retrieved 1 July 2012. by Cat Casey and Alejandra Perez
  14. "What Technology-Assisted Electronic Discovery Teaches Us About The Role Of Humans In Technology - Re-Humanizing Technology-Assisted Review". Forbes. Retrieved 1 July 2012.
  15. Zhao, Lisa. "How Librarian Used E-Resources--An Analysis of Citations in CCQ." Cataloging & Classification Quarterly 42(1) (2006): 117-131.
  16. Lawrence, Steve. Free online availability substantially increases a paper's impact. Nature volume 411 (number 6837) (2001): 521. Also online at http://citeseer.ist.psu.edu/online-nature01/