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

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peek into the discursive construction of the Google Search Algorithm: A critical discourse analysis ( peek-into-discursive-construction-google-search-algorithm-cr )

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algorithm input user output code other data, such as index Figure 3 The algorithm as a whole network of codes, inputs, outputs and engaged users. Note that developers, or other possible actors, are not even included. Note that the output affects the user, but the user also engages with the output, which has a possible effect on the algorithm, and also on the rankings (below). In this simplified scenario, the algorithm includes input, output, as well as user behaviour and user information. Algorithm and (external) data are, thus, inextricably linked. As Sandvig et al. argue: the algorithm needs data, otherwise disclosure of algorithms would not mean anything, since algorithms may only produce specific output in the context of a particular data set (Sandvig et al. 2014, 10). If you would want to study an algorithm, you therefore also need to know what data is used to see how the algorithm works. Naturally, the real Google Search algorithm is much more complex than outlined in Figure 3 since it is based on more than 200 ‘signals’ and other algorithms such as Google’s PageRank (“Algorithms” 2015). 1.2 Current discussions on search algorithms As can be seen from the simplified diagram, many connections are established between different actors, which complicates studying ‘the search algorithm’, or even the Google Search Algorithm, as if it were a static object. The algorithm, in this sense, is rather a networked object. Research has focused on various parts of this ‘algorithmic network’, such as studies that focus on output and user. The following overview of previous studies on search algorithms, bias and discrimination shows just how complex the topic of the search algorithm is and the many perspectives to it, which are all in a way connected. 17

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