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The Dynamic Interest in Topics within the Biomedical Scientific Community

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  • Frederic Michon
  • Mark Tummers

Abstract

The increase in the size of the scientific community created an explosion in scientific production. We have analyzed the dynamics of biomedical scientific output during 1957–2007 by applying a bibliometric analysis of the PubMed database using different keywords representing specific biomedical topics. With the assumption that increased scientific interest will result in increased scientific output, we compared the output of specific topics to that of all scientific output. This analysis resulted in three broad categories of topics; those that follow the general trend of all scientific output, those that show highly variable output, and attractive topics which are new and grow explosively. The analysis of the citation impact of the scientific output resulted in a typical longtail distribution: the majority of journals and articles are of very low impact. This distribution has remained unchanged since 1957, although the interests of scientists must have shifted in this period. We therefore analyzed the distribution of articles in top journals and lower impact journals over time for the attractive topics. Novelty is rewarded by publication in top journals. Over time more articles are published in low impact journals progressively creating the longtail distribution, signifying acceptance of the topic by the community. There can be a gap of years between novelty and acceptance. Within topics temporary novelty is created with new subtopics. In conclusion, the longtail distribution is the foundation of the scientific output of the scientific community and can be used to examine different aspects of science practice.

Suggested Citation

  • Frederic Michon & Mark Tummers, 2009. "The Dynamic Interest in Topics within the Biomedical Scientific Community," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-11, August.
    • Handle: RePEc:plo:pone00:0006544
    DOI: 10.1371/journal.pone.0006544
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    References listed on IDEAS

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    1. Benoît Godin, 2006. "On the origins of bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(1), pages 109-133, July.
    2. M. F. Perutz, 1999. "Will biomedicine outgrow support?," Nature, Nature, vol. 399(6734), pages 299-301, May.
    3. Erik Postma, 2007. "Inflated Impact Factors? The True Impact of Evolutionary Papers in Non-Evolutionary Journals," PLOS ONE, Public Library of Science, vol. 2(10), pages 1-5, October.
    4. Dag W Aksnes, 2003. "Characteristics of highly cited papers," Research Evaluation, Oxford University Press, vol. 12(3), pages 159-170, December.
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    1. Ronan W Glynn & Ji Z Chin & Michael J Kerin & Karl J Sweeney, 2010. "Representation of Cancer in the Medical Literature - A Bibliometric Analysis," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-8, November.

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