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power in Michel Foucault’s tradition” (Norman Fairclough, Ruth Wodak, Siegfried Jäger), grammar, and social cognition (Teun van Dijk).10 For this study, I have used Fairclough’s approach as a basis for my methodology. As previously indicated, Fairclough’s approach is concerned with theories on power and his approach also includes written text (whereas other CDA approaches are rather concerned with spoken text). His approach to CDA is based on upon Bhaskar’s explanatory critique framework (Fairclough 2001a, 124–125). This framework consists of five stages: Stage 1: Stage 2: Stage 3: Stage 4: Stage 5: Focus upon a social problem which has a semiotic aspect. Identify obstacles to it being tackled, 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) • structural analysis: the order of discourse • interactional analysis • interdiscursive analysis • linguistic and semiotic analysis Consider whether the social order (network of practices) in a sense ‘needs’ the problem. Identify possible ways past the obstacles Reflect critically on the analysis (1-4) (Fairclough 2001a, 124–125) The first stage focuses on defining the problem. What is the problem and for whom is it a problem (Fairclough 2001a, 125)? In this stage of the analysis the researcher needs “to go outside of the text, using academic and non-academic sources to get a sense of its [in this case: the algorithms] social context” (Fairclough 2001a, 129).11 The findings of this part of the analysis have already been described in the introduction and chapter Error! Reference ource not found., “Error! Reference source not found.”, since this analysis was also part of a (preliminary) literature review. To recapitulate: algorithms are part of our lives, even when we are unaware of them; the problem is that we do not know if, when and how algorithms play a role in our (daily) life, since algorithms are opaque and powerful companies try to keep them opaque.12 This lack of transparency is a problem for governments, law enforcers, scholars and the public: governments cannot monitor algorithms, law enforcers idem, scholars do not have access to algorithms to study them—in some cases they are even breaking the law when attempting to study algorithms (Sandvig et al. 2014, 12)—and the public does not know what information about them is collected and used by algorithms and whom has access to that information. This is a problem for all of the above, since abuse of algorithms can go undetected, or unintended problems may arise, such as algorithmic bias. While many studies address this problem and many scholars give suggestions on how to 10 See Meyer (2001, 19–23) for concise overview of these approaches. 11 Context “helps in the interpretative process of linguistic phenomena as well as providing explanations” (Baker and Ellece 2011, 21). 12 With few exceptions, such as Netflix. 28PDF Image | peek into the discursive construction of the Google Search Algorithm: A critical discourse analysis
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