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Structure and infrastructure of infectious agent research literature: SARS

Author

Listed:
  • Ronald N. Kostoff

    (The MITRE Corporation (Ret’d))

  • Stephen A. Morse

    (Center for Disease Control)

Abstract

Text mining was used to extract technical intelligence from the open source global SARS research literature. A SARS-focused query was applied to the Science Citation Index (SCI) (SCI 2008) database for the period 1998–early 2008. The SARS research literature infrastructure (prolific authors, key journals/institutions/countries, most cited authors/journals/documents) was obtained using bibliometrics, and the SARS research literature technical structure (hierarchical taxonomy) was obtained using computational linguistics/document clustering.

Suggested Citation

  • Ronald N. Kostoff & Stephen A. Morse, 2011. "Structure and infrastructure of infectious agent research literature: SARS," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(1), pages 195-209, January.
    • Handle: RePEc:spr:scient:v:86:y:2011:i:1:d:10.1007_s11192-010-0240-6
    DOI: 10.1007/s11192-010-0240-6
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    References listed on IDEAS

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    1. Ronald N. Kostoff & J. Antonio del Río & James A. Humenik & Esther Ofilia García & Ana María Ramírez, 2001. "Citation mining: Integrating text mining and bibliometrics for research user profiling," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 52(13), pages 1148-1156.
    2. Don R. Swanson & Neil R. Smalheiser & A. Bookstein, 2001. "Information discovery from complementary literatures: Categorizing viruses as potential weapons," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 52(10), pages 797-812.
    3. Zhang, Zhibin, 2007. "The outbreak pattern of SARS cases in China as revealed by a mathematical model," Ecological Modelling, Elsevier, vol. 204(3), pages 420-426.
    4. Francis Narin & Dominic Olivastro & Kimberly A. Stevens, 1994. "Bibliometrics/Theory, Practice and Problems," Evaluation Review, , vol. 18(1), pages 65-76, February.
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    Cited by:

    1. Milad Haghani & Pegah Varamini, 2021. "Temporal evolution, most influential studies and sleeping beauties of the coronavirus literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7005-7050, August.
    2. Milad Haghani & Michiel C. J. Bliemer, 2020. "Covid-19 pandemic and the unprecedented mobilisation of scholarly efforts prompted by a health crisis: Scientometric comparisons across SARS, MERS and 2019-nCoV literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2695-2726, December.
    3. Simone Belli & Rogério Mugnaini & Joan Baltà & Ernest Abadal, 2020. "Coronavirus mapping in scientific publications: When science advances rapidly and collectively, is access to this knowledge open to society?," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2661-2685, September.

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