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Be True” 2015), and the search results should be “relevant” (“Ten Things We Know to Be True” 2015; “Answers about Privacy and Security” 2015; “Fighting Spam” 2015; “Policies” 2015). Apparently, these properties are common ideals: they are not explained (what is relevance, for whom is it relevant, why is it relevant (see also Gillespie 2014, 127), or they are repeatedly used as an unexplained argument or mentioned as an important asset, such as the word “free”, as if free products or services are an ultimate goal: Data also helps us show relevant ads, so we can make our services free for everyone. (“Answers about Privacy and Security” 2015) We also use data to show you ads that are relevant and useful, and to keep our services free for everyone. (“Answers about Privacy and Security” 2015) Ads are what enable us to make our services like Search, Gmail, and Maps free for everyone. (“Answers about Privacy and Security” 2015) In addition, we’re hoping to fuel greater innovation for mobile users everywhere with Android, a free, open source mobile platform. (“Ten Things We Know to Be True” 2015) While “free”, for instance, does not occur that often as words such as “new”, it does add up to the creation of some mythical things that we are striving towards. Seamless communication reinforces this idea. It also seems a term that refers to some common ideal. In fact, the idea of seamless communication is not new at all (see for instance: de Vries 2013). Due to time and space restrictions I cannot go further into this interesting topic. The point that I want to make is that the Google corpus has on the one hand gaps with regard to topics that have been addressed as very important, while on the other hand the corpus is full of references to some ideal future. The latter seems to function, whether intentionally or not, as a veil for the former: readers may not even be aware of this gap, because their attention is led elsewhere. 3.3 The representation of the algorithm as a manual and automatic instance As argued in chapter 0, “Defining the search algorithm in context of current debates”, the algorithm can be considered to be the code itself, but it can also be considered the whole network of its actors, including its developers and users. In the close reading analysis, it was found that Google is very explicit in stating which processes include automatic processes and which are processes that are performed manually. This finding raises questions such as: why does Google distinguish in such an explicit way between automatic and manual? What are implications of discursively constructing these as two different processes? It was found that Google implicitly contradicts her own explicit claims about automatic processes and manual processes. On the “Policies” page it is stated in a heading: “Algorithms Over Manual Actions” with the elucidation: “We prefer machine solutions to manually organizing information” (“Policies” 2015). While one would expect to be more 41PDF Image | peek into the discursive construction of the Google Search Algorithm: A critical discourse analysis
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