Quantifying the evolution of a scientific topic: reaction of the academic community to the Chornobyl disaster
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DOI: 10.1007/s11192-015-1820-2
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- 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.
- 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.
- 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.
- 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.
- 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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Keywords
Topic evolution; Terms indentification; Bibliometric analysis; Authorship networks; Interdisciplinarity; Text mining; Chornobyl disaster;All these keywords.
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