Issue Positions through the Discourse Network Analyzer

Material interests can be a powerful predictor for member states positions and consequently explain policy change but suffer from certain limitations. So for instance, it is not clear, which side will be supported by the group of “indifferent” member states and how their positions should be determined. The positions of the institutions such as the European Commission or the European Parliament also cannot be measured by looking at the market structure. Finally, as already mentioned the material variables are rarely used in political science to measure positions or preferences. Nonetheless, there are still not so many alternatives that would enable reliable measurements of policy positions over time (König & Luig, 2012).

Many datasets extract the positions of actors by utilizing expert interviews (Benoit & Laver, 2007), hand coding content analysis (Veen, 2011), roll calls (Hagemann, 2007) or opinion surveys (Hug & König, 2002). More recently, researchers started also to rely on quantitative text

analyses and scaling of interest group positions from their position papers (Klüver, 2009). None of these procedures were however practicable for the operationalization of positions regarding gas market liberalization because I am interested in the positions of member states, institutions and interest groups over a long period of time. The majority of the mentioned data sources were available only for a short period of time. So for example Eurogas provides certain position papers on their homepages but only surrounding the Directive 2003/55/EC. A written request to Eurogas whether position papers regarding other directives could be made accessible was unsuccessful, since Eurogas does not seem to have an electronic archive and the effort of retrieving old position papers would be too large⁵¹. The information on the roll calls in the European Council was also useless, since for the gas directives only decisions when all member states agreed were made public. Therefore, the methods of data collection prevailing in the scholarly literature had to be systematically ruled out.

A possible alternative to approximate the positions of the member states is through Discourse Network Analyzer⁵²(DNA) developed by Philip Leifeld (Leifeld, 2013b; Leifeld & Haunss, 2012), which can help utilize information from available media sources. The method has been applied to analyze discourses, i.e. the constellations of belief systems, and offers new interesting insights into the dynamics of policy change (Leifeld, 2013b). It encodes information in time series and thus is particularly suitable for longitudinal analyses. The question is how it can be used to measure the position of many different actors over a longer period of time.

6.2.2.1 Level of Analysis

The program allows to input text sources and then to code them manually into agreements or disagreements between actors over certain concepts. The level of analysis is statement (Leifeld, 2013b, p. 174) from which an actor and her sentiment towards an issue can be extracted. Given the structure of the program it allows changing of the coding procedure tailored to research needs. So for example, the researcher does not necessary need to concentrate on the belief systems but can expand the analysis to other subsystems. The question is whether the belief system can be broadened to include also an actor’s actions that could indicate actor’s position on a certain issue. Actors’ actions and positions are sometimes difficult to separate. An action, such

51 E-Mail from May 2012.

52 Available through: http://www.philipleifeld.de/discourse-network-analyzer/discourse-network-analyzer-dna.html

[Last access: July 2013].

as blocking an agreement in the European Council indicates disagreement with the proposal on the table. If only statements by the actors are coded, this important information gets lost.

Therefore, to measure issue positions both statements and actions of the actors are used. The Figure 28 depicts schematically the assumption that both statements and actions signal issue positions.

Figure 28 Coding Issue positions given the information in the media

6.2.2.2 Coding

The next step of coding is to define the sources of information. In the context of the European gas market liberalization it is not probable that one news resource consistently reports on the developments of the sector and actors’ positions towards liberalization. It is, therefore, suggested to cover a larger sample of media. For this purposes the databank LexisNexis⁵³ is one of the best available options as it combines a large pool of international news and allows for easy keyword search. The databank was searched for the combinations of words “gas market AND European Union”, “gas market liberalization AND European Union”, “internal gas market AND European Union” in all international sources in English without time constraint. This way over 900 articles were collected starting in April 1991. The results include many different newspapers but given the technicality of the topic, the reports from “Europe Energy”, a segment of Europolitics’

reports, which are provided by the Europe Information service, are the dominant source.

Additionally, comprehensive reports are also offered by “Utility Europe”, provided by Reed Business Information Ltd⁵⁴.

Before continuing with the coding through the DNA another coding procedure had to be defined:

the scope of the issue positions. Basically, there are two possible options: (1) to define the categories of issue positions a priori or (2) to apply inductive approach. Both options have their

53 Access through Institute of Advanced Studies and the University of Konstanz:

http://www.lexisnexis.com/hottopics/lnacademic/ [Last access: March 2013].

54 The overview of all newspaper sources can be checked by looking into the dna.file provided on the CD-Rom.

strengths and weakness but given the longitude and the complexity of the process under consideration, it was decided, similarly to Leifeld (2013) to apply “multipass coding strategy”

(Leifeld, 2013b, p. 177). This implies starting with a small number of predefined categories that are known from the secondary literature and revising the coding scheme when getting new information.

Finally, all articles were hand coded with the Discourse Network Analyzer, which yielded 592 statements, by 275 actors on 87 issues. The data collected this way offers interesting descriptive insights but also allows for computation of variables that can be used in quantitative analyses.

First of all, the data can graphically depict the dynamics through affiliation networks (bipartite graph connecting actors to issues and indicating their agreement or disagreement) or congruence networks (adjacency graph where links are weighted by the number of common concepts)⁵⁵. Moreover, the data contains information on agreement or disagreement of actors on certain issues. Therefore, a variable “level of agreement at time point t” ( ) can be calculated by subtracting number of actors that have voiced disagreement at time point t ( ) from the number of actors that have voiced agreement ( ).

= –

Equation 15 Level of agreement at time point t

It is based on the assumption that if many actors voice agreement over certain issues in the media that it might indicate a broader agreement and possible compromise and if there are many disagreements voiced in the media that there is no policy change to expect soon. Figure 29 depicts the longitudinal development of the media discourse. It is interesting to observe that there were relatively high levels of agreement in the years 2000 and 2003 following a major policy change in 2003. Whether there is any systematic effect will be test in Chapter 6.3

55 Mathematical presentation see Leifeld (2013b, pp. 173-175).

Figure 29 Level of agreement 1991-2010

6.2.2.3 Limitations

The coding steps discussed in chapters 6.2.2.1 and 6.2.2.2 certainly display many limitations.

Given that the operationalization of issue positions relies on media sources, it might reflect only the perceptions of the media arena or follow the so-called media logic and thus not necessary reflect the positions of the member states, institutions or interest groups. Nonetheless, this might present only a marginal problem for the purposes of the analysis. Actors use media to signal their interests to other actors or to bring different issues on the agenda. Therefore, it can be assumed that information contained in the media is comparable with the information contained in the position papers.

Additionally, there is a problem of reliability as a single researcher has coded the data. An alternative where few researchers would code the same text was not available within the scope of this analysis. However, the quality of the coding can be assessed by comparing the results with the results from the secondary literature that has used interviews to gather information on the positions of member states (Eikeland, 2011) and by tracing the process in the dynamics of actors’

positions as will be discussed in chapter 6.3.1. So for instance, if one actor displays many inconsistencies in her issue positions this might indicate possible inconsistencies in the coding or the source of information (similar idea in Leifeld (2013b)).