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proposed, scholars also acknowledge that disclosure is not realistic, since that would open the way for spammers and hackers (e.g. Sandvig et al. 2014, 9; Introna and Nissenbaum 1999, 34; Granka 2010, 366). Sandvig et al., for instance, argue that public disclosure of algorithms “might be likely to produce serious negative consequences” (2014, 9). They add: On many platforms the algorithm designers constantly operate a game of cat-and-mouse with those who would abuse or “game” their algorithm. These adversaries may themselves be criminals (such as spammers or hackers) and aiding them could conceivably be a greater harm than detecting unfair discrimination in the platform itself. (Sandvig et al. 2014, 9) Scholars seem to depart from the assumption that algorithms need to be opaque to a certain extent to prevent abuse. Yet, is this need really true, or is it just an example of powerful framing of algorithms? Why do scholars accept not giving full disclosure that easily? This thesis seeks to understand how Google uses discourse to construct, maintain and reinforce assumptions and presuppositions concerning the politics of the algorithm—such as the assumption that algorithms must be opaque to avoid abuse by spammers. In other words: how is the Google Search algorithm discursively constructed in relation to user choice, bias, transparency, and what are implications of this discursive construction for the conservation of power relations between Google and its users? To answer this question, I have used theory and methodology borrowed from Critical Discourse Analysis (CDA). A corpus of Google texts was composed, on which I performed quantitative and qualitative analysis. The quantitative analysis entailed word frequency queries, while the qualitative analysis was done by close reading as a part of Norman Fairclough’s approach of CDA. In chapter 2 I will describe the methodology more extensively. It was decided to focus on the Google Search algorithm specific, since it is the most used search engine by people worldwide. It is thereby one of the most used mediators between user and knowledge. This means that possible discursive constructions of this algorithm have huge user impact and reach. Firstly, in chapter 1 (“Defining the search algorithm in context of current debates“) I will elaborate on the algorithm, what it is and why studying ‘the algorithm’ is complex. Is there such a thing as ‘the algorithm’, for instance? I will also outline and extend on previous research on search algorithms to understand how my research is positioned in current discussions on the algorithm and to understand the context that is needed to later interpret the findings from the qualitative analysis. In the subsequent chapter (“Methodology and methods”) the CDA methodology, including its theoretical underpinnings will be discussed, which includes concepts such as power, hegemony, discourse, and language (chapter 2.1 “Theoretical underpinnings”). In this first section also the used methodology, Critical Discourse Analysis, will be discussed: its history, its critique, and the specific approach of CDA that was used in this study, namely Norman Fairclough’s. The second section (chapter 2.2 “Methods of data collection and analysis”) describes the methods of data collection and data analysis of the quantitative and qualitative methods. In the subsequent chapter (chapter 14PDF Image | peek into the discursive construction of the Google Search Algorithm: A critical discourse analysis
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