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Big Data Analysis of Public Acceptance of Nuclear Power in Korea

  • Roh, Seungkook (Policy Research Division, Korea Atomic Energy Research Institute (KAERI))
  • Received : 2016.07.04
  • Accepted : 2016.12.29
  • Published : 2017.08.25

Abstract

Public acceptance of nuclear power is important for the government, the major stakeholder of the industry, because consensus is required to drive actions. It is therefore no coincidence that the governments of nations operating nuclear reactors are endeavoring to enhance public acceptance of nuclear power, as better acceptance allows stable power generation and peaceful processing of nuclear wastes produced from nuclear reactors. Past research, however, has been limited to epistemological measurements using methods such as the Likert scale. In this research, we propose big data analysis as an attractive alternative and attempt to identify the attitudes of the public on nuclear power. Specifically, we used common big data analyses to analyze consumer opinions via SNS (Social Networking Services), using keyword analysis and opinion analysis. The keyword analysis identified the attitudes of the public toward nuclear power. The public felt positive toward nuclear power when Korea successfully exported nuclear reactors to the United Arab Emirates. With the Fukushima accident in 2011 and certain supplier scandals in 2012, however, the image of nuclear power was degraded and the negative image continues. It is recommended that the government focus on developing useful businesses and use cases of nuclear power in order to improve public acceptance.

Keywords

References

  1. S.-H. Park, W.-J. Jung, T.-H. Kim, S.-Y. Tom Lee, Can renewable energy replace nuclear power in Korea? An economic valuation analysis, Nucl. Eng. Technol. 48 (2016) 559-571. https://doi.org/10.1016/j.net.2015.12.012
  2. H.-G. Kim, J.-H. Yang, W.-J. Kim, Y.-H. Koo, Development status of accident-tolerant fuel for light water reactors in Korea, Nucl. Eng. Technol. 48 (2016) 1-15. https://doi.org/10.1016/j.net.2015.11.011
  3. R. Wustenhagen, M. Wolsink, J. Burer, Social acceptance of renewable energy innovation: an introduction to the concept, Energy Policy 35 (2007) 2683-2691. https://doi.org/10.1016/j.enpol.2006.12.001
  4. P.E. Slovic, The Perception of Risk, Earthscan Publications, London, 2000.
  5. L. Sjoberg, B.-M. Drottz-Sjoberg, Public risk perception of nuclear waste, Int. J. Risk Assess. Manag. 11 (2009) 248-280.
  6. M. Graham, T. Shelton, Geography and the future of big data, big data and the future of geography, Dialogues Hum. Geogr. 3 (2013) 255-261. https://doi.org/10.1177/2043820613513121
  7. M. Johnson, Timepieces: components of survey question response latencies, Polit. Psychol. 25 (2004) 679-702. https://doi.org/10.1111/j.1467-9221.2004.00393.x
  8. S. Bergsma, M. Dredze, B. Van Durme, T. Wilson, D. Yarowsky. Broadly improving user classification via communication-based name and location clustering on Twitter, in HLT-NAACL, 2013.
  9. M. Pennacchiotti, A.-M. Popescu, A machine learning approach to Twitter user classification, ICWSM 11 (2011) 281-288.
  10. K. Ikeda, G. Hattori, C. Ono, H. Asoh, T. Higashino, Twitter user profiling based on text and community mining for market analysis, Knowledge-Based Syst 51 (2013) 35-47. https://doi.org/10.1016/j.knosys.2013.06.020

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