Initial coding and codebook development

After they were fully transcribed, all interviews were imported into NVivo10 for analysis. They were associated with their groups of reference (politicians, journalists, press officers) in order to facilitate future queries. All interviews were

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analysed using successive stages of coding and aiming to develop analytical insight grounded in the generated data. The word ‘data’ refers in this context to the “textual representation of a conversation, observation and interaction” (Guest et al., 2012: 50).

Coding refers to the process through which textual data generated for analysis is de-constructed in multiple units of meaning or incidents – actions, characteristics, experiences, explanations – with the aim of assisting analytical thinking about that data (Charmaz 2006; Strauss & Corbin 2008; Birks & Mills 2011). It acts as a way to “define what is happening in the data and begin to grapple what it means” (Charmaz, 2006: 46). The initial stage of coding for this study was developed following a line-by-line approach, that is to say subjecting a first group of interviews (N= 14) to close inspection and developing open, rather than hierarchically organised, codes. Each time a code is created it has to be defined, aiming for consistency in the future application of that code to different data segments (see complete Code Book in Appendix 4). Following this approach, it was typical for a paragraph to include more than one, eventually overlapping, codes. For example, the following paragraph (from a conversation with the editor of an online newspaper) has been coded with 3 different nodes: “symbiosis-synchrony”, referring to the convergence between political and journalistic interests; “political operation”, referring to a source’s coordinated effort to get media coverage with a strategic aim; and “assessing quality of information”, referring to the journalistic practice of checking the veracity of the information provided.

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So there you have an example of someone who is trying to operate and, despite that he is trying to operate, the issue is anyway real, is truthful, is not an invention and is news. So, what we do in such case is talk to all the sources. Journalist 2, Editor, online media.

In the following example, extracted from the conversation with a senator, the paragraph has been also coded into three nodes: “media ownership- concentration”, referring to the concentration of media property; “triggering debate”, referring to the political actor’s aims of seeking media coverage to position a topic on the agenda and “acknowledging difficulties”, referring to the recognition that such an aim is not always easy to achieve:

Sometimes we speak about issues that we are interested in positioning in the media, which is not very easy because all media here is concentrated, so this is not an open thing in which everyone has the same communication possibilities.

Politician 11, Senator.

The objective of this strategy for initial coding is to stick closely to the data and interrogate participants’ experiences instead of applying pre-existent categories (Charmaz 2006); “a brainstorming approach to analysis” (Strauss & Corbin, 2008: 160).

After coding an initial group of six interviews following this approach, a total of 115 codes were organised in a tree code in order to facilitate the localization of specific codes in the analysis of successive interviews, providing an initial framework for data organisation and analysis. Codes were organised into six groups or domains, identified with a colour to facilitate visual identifications: political actors’ domain (blue nodes), journalists’ domain (red nodes), interactions between politicians and journalists (purple nodes), agenda drivers (green nodes), contextual features (orange nodes) and actors (yellow nodes). Each domain generally contained a handful of categories or higher-level concepts under which

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lower-level concepts were organised according to shared properties (Strauss & Corbin 2008).

Nodes were constantly revised for consistency, in order to rename, reorganise or merge redundant nodes. However, new nodes only occasionally emerged after coding the first dozen interviews, confirming the validity of this threshold as a point of reference for data saturation (see Guest et al., 2006). Anticipating this scenario, the interviews first coded were those identified (during field work-level analysis) as richer in detail and example. Subsequently, analysis moved forward in groups of three, intercalating interviews from the different groups of reference (politicians, journalists, press officers). Since longer and richer interviews were analysed at the beginning of the process, coding of subsequent interviews became more straightforward; most codes had already been identified and later interviews analysed tended to be those that were shorter. The final number of nodes after the completion of initial coding in all interviews was 129.

Memo-writing was a fundamental tool during data analysis. Memo-writing is especially encouraged within the grounded theory tradition as a way to explore data and identify relations between nodes – the basis for data analysis and early theorisation – as well as a way of monitoring the relationship between emergent categories and research questions (Charmaz 2006; Strauss & Corbin 2008; Birks & Mills 2011).

The following image shows a screenshot from NVivo with the first stage tree node, as it looks when the nodes are not expanded. On the following page there is a diagram showing all nodes identified during the first stage of coding, organised in six domains identified with a colour to facilitate the coding process.

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Figure 9: First Node Tree not expanded (see full diagram of nodes in next page)

161 Fig u re 1 0 : Di ag ra m o f f ir st n o d e t re e ex p an d ed

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