peek into the discursive construction of the Google Search Algorithm: A critical discourse analysis

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Figure 5: Treemap visualization of the data in table 2, made with Raw (Caviglia et al., n.d.). The sizes of the boxes present the weight percentage of the designated word. The green visualizes the weighed percentage in the Google corpus, while the blue parts indicate the weighed percentage of the designated word in the academic corpus. As can be seen in Table 2, there is no explicit mention of bias, discrimination, ethics or responsibility in the Google corpus. Google does not mention opacity, however, transparency is mentioned. It is used in sentences that refer to Google’s transparency report, which I decided to not include in the Google corpus for this study, since it focuses on what Google does or not do with its data, such as giving user information to governments (“Access to Information” 2015), while the focus of this study is rather the discourse on transparency of the workings of the algorithm. While Google does not go into issues of transparency in relation to the workings of its algorithm, Google is transparent, however superfluously, about properties about and processes that concern its search algorithm, such as that the Google search algorithm uses more than 200 signals (“Algorithms” 2015) and 39

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