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Exploring Signals for a Nuclear Future Using Social Big Data

Author

Listed:
  • Seungkook Roh

    (Department of Public Administration, Korean National Police University, 100-50 Hwangsan-gil, Sinchang-myeon, Asan, Chungcheongnam-do 31539, Korea)

  • Jae Young Choi

    (Department of Nuclear & Quantum Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea)

Abstract

Since the start of the new Korean government in 2017, the Korean nuclear energy system has undergone a major change. This change in national energy policy can be forecasted by analyzing social big data. This study verifies whether future forecasting methodologies using weak signals can be applied to Korean nuclear energy through text mining the data of web news between 2005 and 2018, comparing and applying the methodology to notable events (i.e., the UAE nuclear power plant (NPP) contract and nuclear phase-out). In addition, we predict what changes will be made in the Korean nuclear energy system post-2019. Keywords extracted through text mining were quantitatively classified into a weak signal or a strong signal using a Keyword Emergence Map (KEM) and a Keyword Issue Map (KIM). The extracted keywords predicted the contract of the UAE NPPs in 2009 and nuclear phase-out in 2017. Furthermore, keywords revealing future signals beyond 2019 were found to be ‘nuclear phase-out’ and ‘wind energy’. The weak-signal methodology can be applied as a tool to predict future energy trends during the current circumstance of the rapidly changing world energy market.

Suggested Citation

  • Seungkook Roh & Jae Young Choi, 2020. "Exploring Signals for a Nuclear Future Using Social Big Data," Sustainability, MDPI, vol. 12(14), pages 1-16, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:14:p:5563-:d:382723
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    References listed on IDEAS

    as
    1. Seungkook Roh & Jin Won Lee & Qingchang Li, 2019. "Effects of Rank-Ordered Feature Perceptions of Energy Sources on the Choice of the Most Acceptable Power Plant for a Neighborhood: An Investigation Using a South Korean Nationwide Sample," Sustainability, MDPI, vol. 11(6), pages 1-21, March.
    2. Oded Netzer & Ronen Feldman & Jacob Goldenberg & Moshe Fresko, 2012. "Mine Your Own Business: Market-Structure Surveillance Through Text Mining," Marketing Science, INFORMS, vol. 31(3), pages 521-543, May.
    3. Guo, Yue & Ren, Tao, 2017. "When it is unfamiliar to me: Local acceptance of planned nuclear power plants in China in the post-fukushima era," Energy Policy, Elsevier, vol. 100(C), pages 113-125.
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    Cited by:

    1. Chankook Park & Minkyu Kim, 2021. "A Study on the Characteristics of Academic Topics Related to Renewable Energy Using the Structural Topic Modeling and the Weak Signal Concept," Energies, MDPI, vol. 14(5), pages 1-24, March.
    2. Minkyu Kim & Chankook Park, 2021. "Academic Topics Related to Household Energy Consumption Using the Future Sign Detection Technique," Energies, MDPI, vol. 14(24), pages 1-24, December.
    3. Wei Sun & Chao Xu & Yi-Zhen Wang & Sui-Zheng Qiu & Yu-Sheng Liu & Hao Fu, 2021. "BEPU Analysis in LBLOCA Safety Review Calculation," Sustainability, MDPI, vol. 13(24), pages 1-13, December.

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