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Quantifying the evolution of a scientific topic: reaction of the academic community to the Chornobyl disaster

Author

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  • O. Mryglod

    (Institute for Condensed Matter Physics of the National Academy of Sciences of Ukraine)

  • Yu. Holovatch

    (Institute for Condensed Matter Physics of the National Academy of Sciences of Ukraine)

  • R. Kenna

    (Coventry University)

  • B. Berche

    (Université de Lorraine)

Abstract

We analyze the reaction of academic communities to a particular urgent topic which abruptly arises as a scientific problem. To this end, we have chosen the disaster that occurred in 1986 in Chornobyl (Chernobyl), Ukraine, considered as one of the most devastating nuclear power plant accidents in history. The academic response is evaluated using scientific-publication data concerning the disaster using the Scopus database to present the picture on an international scale and the bibliographic database “Ukrainika naukova” to consider it on a national level. We measured distributions of papers in different scientific fields, their growth rates and properties of co-authorship networks. Elements of descriptive statistics and tools of complex network theory are used to highlight the interdisciplinary as well as international effects. Our analysis allows comparison of contributions of the international community to Chornobyl-related research as well as integration of Ukraine in international research on this subject. Furthermore, the content analysis of titles and abstracts of the publications allowed detection of the most important terms used for description of Chornobyl-related problems.

Suggested Citation

  • O. Mryglod & Yu. Holovatch & R. Kenna & B. Berche, 2016. "Quantifying the evolution of a scientific topic: reaction of the academic community to the Chornobyl disaster," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 1151-1166, March.
    • Handle: RePEc:spr:scient:v:106:y:2016:i:3:d:10.1007_s11192-015-1820-2
    DOI: 10.1007/s11192-015-1820-2
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    References listed on IDEAS

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    Cited by:

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    3. R. Basurto-Flores & L. Guzmán-Vargas & S. Velasco & A. Medina & A. Calvo Hernandez, 2018. "On entropy research analysis: cross-disciplinary knowledge transfer," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 123-139, October.
    4. Meijun Liu & Yi Bu & Chongyan Chen & Jian Xu & Daifeng Li & Yan Leng & Richard B. Freeman & Eric T. Meyer & Wonjin Yoon & Mujeen Sung & Minbyul Jeong & Jinhyuk Lee & Jaewoo Kang & Chao Min & Min Song , 2022. "Pandemics are catalysts of scientific novelty: Evidence from COVID‐19," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(8), pages 1065-1078, August.
    5. Sichao Tong & Per Ahlgren, 2017. "Evolution of three Nobel Prize themes and a Nobel snub theme in chemistry: a bibliometric study with focus on international collaboration," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 75-90, July.
    6. Kiran Kaur & Kwan Hoong Ng & Ray Kemp & Yin Yee Ong & Zaharah Ramly & Ai Peng Koh, 2019. "Knowledge generation in the wake of the Fukushima Daiichi nuclear power plant disaster," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 149-169, April.
    7. Christian Mühlroth & Michael Grottke, 2018. "A systematic literature review of mining weak signals and trends for corporate foresight," Journal of Business Economics, Springer, vol. 88(5), pages 643-687, July.

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