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The distribution of references across texts: Some implications for citation analysis

Author

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  • Ding, Ying
  • Liu, Xiaozhong
  • Guo, Chun
  • Cronin, Blaise

Abstract

In citation network analysis, complex behavior is reduced to a simple edge, namely, node A cites node B. The implicit assumption is that A is giving credit to, or acknowledging, B. It is also the case that the contributions of all citations are treated equally, even though some citations appear multiply in a text and others appear only once. In this study, we apply text-mining algorithms to a relatively large dataset (866 information science articles containing 32,496 bibliographic references) to demonstrate the differential contributions made by references. We (1) look at the placement of citations across the different sections of a journal article, and (2) identify highly cited works using two different counting methods (CountOne and CountX). We find that (1) the most highly cited works appear in the Introduction and Literature Review sections of citing papers, and (2) the citation rankings produced by CountOne and CountX differ. That is to say, counting the number of times a bibliographic reference is cited in a paper rather than treating all references the same no matter how many times they are invoked in the citing article reveals the differential contributions made by the cited works to the citing paper.

Suggested Citation

  • Ding, Ying & Liu, Xiaozhong & Guo, Chun & Cronin, Blaise, 2013. "The distribution of references across texts: Some implications for citation analysis," Journal of Informetrics, Elsevier, vol. 7(3), pages 583-592.
    • Handle: RePEc:eee:infome:v:7:y:2013:i:3:p:583-592
    DOI: 10.1016/j.joi.2013.03.003
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    References listed on IDEAS

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    1. Ying Ding, 2011. "Applying weighted PageRank to author citation networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(2), pages 236-245, February.
    2. Blaise Cronin, 2004. "Normative shaping of scientific practice: The magic of Merton," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(1), pages 41-46, May.
    3. Ying Ding, 2011. "Applying weighted PageRank to author citation networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(2), pages 236-245, February.
    4. Ben‐Ami Lipetz, 1965. "Improvement of the selectivity of citation indexes to science literature through inclusion of citation relationship indicators," American Documentation, Wiley Blackwell, vol. 16(2), pages 81-90, April.
    5. Gertrud Herlach, 1978. "Can retrieval of information from citation indexes be simplified? Multiple mention of a reference as a characteristic of the link between cited and citing article," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 29(6), pages 308-310, November.
    6. Henry Small, 2011. "Interpreting maps of science using citation context sentiments: a preliminary investigation," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(2), pages 373-388, May.
    7. Charles Oppenheim & Susan P. Renn, 1978. "Highly cited old papers and the reasons why they continue to be cited," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 29(5), pages 225-231, September.
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