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 metaissue 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.

A new approach to semantic sustainability assessment: text mining via network analysis revealing transition patterns in German municipal climate action plans

“…Various other data analysis methods might also be considered. Different kinds of semantic network analysis and the corresponding network metrics, see, e.g., Doerfel [48], Diesner [124], or Shim et al [125], could provide additional insights on local networks. Furthermore, clustering algorithms could be used, e.g., to identify typologies of MCAPs.…”

Of Uranium and Carbon: Divergence of Energy Policy in Germany and France

“…Stefes notes SPD-the Green coalition's successful negotiation with German power utilities to phase out nuclear power plants (p. 159). Shim, Park, and Wilding (2015) note that in 1998, the SPD-Green coalition government had proposed the phase out of nuclear energy in Germany by 2022; however, in 2009, Chancellor Merkel from the Christian Democratic Union (CDU) announced a 12-year delay. The federal government argued, "the phaseout would present huge challenges for the national economy and industrial structure," and nuclear power would remain as a "bridging technology" to the future (Shim et al, 2015, p. 54).…”

Mapping discursive dynamics of the financial crisis: a structural perspective of concept roles in semantic networks

“…11, we display multidimensional scalings (MDS) in two dimensions for both the ECB and Fed correlation matrices. 7 The correlations were converted to distances via a 1 − r transformation where r is a period pairwise Pearson correlation. In MDS, an eigen-decomposition reduces the dimensionality of a matrix of distances (in our case, the extent of non-correlation) such that a pairwise distance between each pair of data points in the reduced space (in our case, 2-D) is roughly proportional to the original distance between the pair.…”

“…Successful application of semantic network analysis to a variety of corpora addressing a multitude of contexts attests to the flexibility and adaptability of this method. A few examples can be found in the works of Leydesdorff and Welbers on co-words in context [5]; Doerfel and Barnett on the structure of the International Communication Association (ICA) [6]; Shim, Park, and Wilding on nuclear energy policy frames [7]; Danowski on mapping publics of a business [8]; Carley and Kaufer on symbols and symbolic activity [9]; Grebitus and Bruhn on the perception of food quality [10]; Kleinnijenhuis, Hoof, Oegema, and Ridder on the effects of news on voting [11]; Kim on Internet discourses of Korean supporters of Hwang Woo Suk [12]; Leydesdorff and Hellsten on the role of language in tracking the way stem cell research is represented in various contexts [13]; Leydesdorff and Hellsten on metaphors and diaphors in scientific controversies [14]; and Nerghes, Hellsten, and Groenewegen on the evolution of metaphor families in media reports [15].…”

“…One such effort comes from Carley and Kaufer [9], which combines density, conductivity, and consensus to explore connectivity in semantic networks. A recent study [7] examines structural roles of concepts alternatively using raw centrality measures. The paper of Huang, Lv, Zhang, Yang, Zheng, and Wen [33] proposes a combination of three strongly correlated social network analysis (SNA) metrics (degree, ego-betweenness centrality, and eigenvector centrality) to evaluate only those top-ranked nodes (core nodes and bridge nodes) in undirected binary networks.…”