Identifying policy frames through semantic network analysis: an examination of nuclear energy policy across six countries

Abstract

This study uses semantic network analysis to investigate nuclear energy policy frames in six countries: USA, UK, Germany, France, Japan, and South Korea. It is suggested that semantic network analysis represents a useful tool to investigate policy frames in complex policy environments. The discourse of top-level decision-makers is analyzed to highlight similarities and differences in policy frames and to identify the key policy arguments in the integrated network of all six countries. In total, 14 major policy arguments are identified, which relate to the three major frames of energy security, clean energy, and nuclear safety, along with the meta-issue of economic growth. There are differences in the degree of emphasis on each of the frames in the six countries, and Germany can be seen to have diverged the most following the Fukushima accident, as the emphasis is on clean energy, to the exclusion of the other frames. In contrast, both the USA and Japan have framed the issues primarily in terms of nuclear safety and energy security, while the UK and France have stressed the economic growth frame, and Korea has prioritized nuclear safety.

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Notes

  1. 1.

    Similarly, Salisbury (2001) and Sherblom et al. (2001) analyzed salient words, image, cognitive construct, and meanings using neural network content analysis.

  2. 2.

    Statistical analysis techniques such as multidimensional scaling (MDS), cluster analysis, correspondence analysis, discriminant analysis (Jang and Barnett 1994), correlation analysis, and spatial modeling as a more advance version of MDS (Kwon et al. 2009) can also be used for determining relations among concepts and grouping them through statistical analyses.

  3. 3.

    BCI measures how centralized the betweenness of the set of actors is (i.e., whether communication in the community depends on one member or many). A BCI reaches its maximum value of 1 when all actors in the network are dependent on one actor to communicate with each other and “its minimum value (0) occurs when all actors have exactly the same actor betweenness index” (Wasserman and Faust 1994: 192).

  4. 4.

    For example, in the case of Germany, excerpts from an energy summit speech (April 15, 2011) and an interview with Zeit (May 12, 2011) were combined for post-Fukushima accident frame analysis, while interviews with FAZ (February 25, 2010), Bild am Sonntag (June 13, 2010), Frage (July 7, 2010), Süddeutsche Zeitung (September 29, 2010), and Focus (November 8, 2010) were combined for pre-Fukushima accident frame analysis.

  5. 5.

    The following definition of sentence was used: “a grammatical unit consisting of one or more words that are grammatically linked. A sentence can include words grouped meaningfully to express a statement, question, exclamation, request, command or suggestion” (http://en.wikipedia.org/wiki/Sentence_(linguistics).

  6. 6.

    A coding example is illustrated in Appendix 4.

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Acknowledgments

This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2013S1A3A2055108).

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Correspondence to Chisung Park.

Appendices

Appendix 1

See Table 10.

Table 10 Comparison of nuclear energy among six countries

Appendix 2

See Table 11.

Table 11 Network properties: prior to the Fukushima accidenta

Appendix 3

See Table 12.

Table 12 Influential concepts in the four largest communities of the four countries: prior to the Fukushima accident

Appendix 4: Example of coding

Original text (a sentence): While nuclear energy has the advantages of being an inexpensive and clean energy source, it is with greater confidence in its safety that it can be more widely used.

Converted to: nuclear energy advantage inexpensive clean energy source greater confidence safety widely use.

Each word is defined as a node. Then, two consecutive words are connected; nuclear-energy, energy-advantage, advantage-inexpensive…. safety-widely, widely-use.

Appendix 5

See Table 13.

Table 13 Data collection for semantic network analysis by the six countries

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Shim, J., Park, C. & Wilding, M. Identifying policy frames through semantic network analysis: an examination of nuclear energy policy across six countries. Policy Sci 48, 51–83 (2015). https://doi.org/10.1007/s11077-015-9211-3

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Keywords

  • Policy frame
  • Text network analysis
  • Frame analysis
  • Nuclear energy policy