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proceed, it seems that the lack of disclosure of algorithm is in a way accepted, though reluctantly: transparency leads to abuse, seems to be the core of many arguments (e.g. Sandvig et al. 2014, 9; Introna and Nissenbaum 1999, 34; Granka 2010, 366). It is as if this idea is unquestionable, a fact. The problem is that possible future ways to deal with algorithmic transparency are beforehand (partly) excluded as possibility, since the algorithm must remain (partly) opaque. This ‘fact’ gives power to owners and developers of algorithms. Apart from looking at the context of the algorithm, we need to look at the kind of discourse in which the algorithm is imbedded, to understand whether there are powerful agents that maintain the problem of opacity. The second stage in the framework concerns identification of the problems that need to be tackled. This can be done through analysis of: a) “The network of practices it is located within”, b) “The relationship of semiosis to other elements within the particular practice(s) concerned”, c “the discourse (the semiosis itself)” (Fairclough 2001a, 125). I understand this stage as putting the texts into context (into the whole) in a heuristic way and then focus on its parts, by performing a semiotic analysis. The first two steps of stage two are part of contextualising the problem, as I have already done in earlier chapters: in chapter 1.1 “What is an algorithm? What is considered (part of) an algorithm?” I have elaborated on the actors that are present in the algorithmic network and how these are all intertwined. In chapter 1.2 “Current discussions on search algorithms” I have outlined how discussions on search algorithms touch upon other problems, such as bias and discrimination. The last step in the second stage is the semiosis: the actual analysis of the texts itself. Whereas step one and two in this stage where looking at the texts within the whole (its context), this steps zooms in on the texts itself. This step consists of four parts. These are: structural analysis (the order of discourse), interactional analysis, interdiscursive analysis, and linguistic and semiotic analysis (Fairclough 2001a, 125). Structural analysis is concerned with how language is used in interaction to structure or influence, for example: “the way in which managerial discourse has colonized public service domains such as education” (Fairclough 2001a, 126). Interactional analysis consists of interdiscursive analysis and linguistic and semiotic analysis. In short: texts are interactive even if they are written—in which case the interactants are distant. Interdiscursive analysis covers analysing how different genres, discourse and styles are used together in articulations. Linguistic and semiotic analysis strongly rely on linguistic categories: “the core operationalizations depend on linguistic concepts such as actors, mode, time, tense, argumentation, and so on” (Meyer 2001, 25). This third step (the discourse itself) with its four parts are the core of my thesis and can be found in the next chapter (Chapter 3: “Analysis/ interpretation”). There is no clear distinction between the process of data collection and analysis: “CDA sees itself more in the tradition of Grounded Theory where data collection is not a phase that must be finished before analysis starts but might be a permanently ongoing procedure” (Meyer 2001, 18; Meyer 2001, 23–24). Also, CDA lacks a specific way of collecting data (Meyer 2001, 23). Therefore, the last step in the second stage (the step that consisted of the four aforementioned parts: structural analysis, interdiscursive analysis, linguistic and semiotic 29PDF Image | peek into the discursive construction of the Google Search Algorithm: A critical discourse analysis
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