{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"1d3bd28e-c1ba-4af2-8580-60b32ef26053","title":"If...Then Algorithmic Power and Politics","author":null,"edition":null,"publisher":null,"year":null,"isbn":"2017054909","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"1d3bd28e-c1ba-4af2-8580-60b32ef26053","id":"1d3bd28e-c1ba-4af2-8580-60b32ef26053","uuid":"1d3bd28e-c1ba-4af2-8580-60b32ef26053","title":"If...Then Algorithmic Power and Politics","normalized_title":"ifthenalgorithmicpowerandpolitics","author":null,"edition":null,"publisher":null,"year":null,"isbn":"2017054909","isbns":["2017054909","9780190493042","9780190493059"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":211,"navigation_url":"https://workshop.closeclaw.top/ai/book/1d3bd28e-c1ba-4af2-8580-60b32ef26053","title_url":"https://workshop.closeclaw.top/ai/title/If...Then%20Algorithmic%20Power%20and%20Politics","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/1d3bd28e-c1ba-4af2-8580-60b32ef26053/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/1d3bd28e-c1ba-4af2-8580-60b32ef26053/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/1d3bd28e-c1ba-4af2-8580-60b32ef26053","page_url":"https://workshop.closeclaw.top/api/ai/books/1d3bd28e-c1ba-4af2-8580-60b32ef26053/page","search_url":"https://workshop.closeclaw.top/api/ai/books/1d3bd28e-c1ba-4af2-8580-60b32ef26053/search"},"page":{"printed_page":85,"pdf_page":95,"physical_index":95,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"2bfb22a8bd1529c996b6c16e41ffae49f3835491d382608c1feeb1e17008e5d9"},"chapter":"IF...THEN","content":"(Foucault, 1977: 148). Just as with the specific machines (i.e., military, prisons, hospitals) described by Foucault, it is not the actual individual that counts in Facebook. This is why spaces are designed in such a way as to make individuals interchangeable. The generic template structure of Facebook’s user profiles provide not so much a space for specific individuals but a space that makes the structured organization of individuals’ data easier and more manageable. The system, then, does not particularly care for the individual user as much as it thrives on the decomposition and recomposition of the data that users provide. However, whereas the architecture of  the Panopticon makes all inmates equally subject to permanent visibility, the Facebook algorithm does not treat subjects equally; it prioritizes some above others. Whereas visibility, as a consequence of the panoptic arrangement, is abundant and experienced more like a threat imposed from outside powers, visibility in the Facebook system arguably works the opposite way. The algorithmic architecture of the news feed algorithm does not automatically impose visibility on all subjects. Visibility is not something ubiquitous but rather something scarce. As content, users, and activities on the Facebook platform grow and expand, visibility becomes even scarcer. According to Brian Boland (2014), who leads the Ads Product Marketing team at Facebook, this means that “competition in news feed is increasing” and that it is “becoming harder for any story to gain exposure in news feed.”\n\nIn order to see how many posts actually made it to the news feed, I conducted an experiment of what could be considered a process of “reversed engineering.”18 Recall how it was claimed in the previous chapter that the first step in knowing algorithms is not to regard the impossibility of seeing inside the black box as an epistemological limit. Instead, what I termed a “technographic inquiry” starts by asking what algorithms are suggestive of by observing the outcomes of algorithmic procedures as indicative of its “point of view.” Over the course of several months (March-September, 2011), I used my own personal Facebook profile to compare the contents of the “top news” to that of the “most recent.” The most intensive investigation took place during April 2011 when I did the comparison a couple of times a week, took screen shots of the entire top news feeds, and manually counted the posts in the most recent feeds. I took the oldest story published in the top news and compared it to the number of stories published in the most recent feed up to the same time stamp. On a randomly selected day in April 2011, this amounted to 280 stories/updates published on the most recent feed as opposed to 45 posts appearing in the top news feed within the same timeframe. At first glance, only 16% of the possible stories seem to have made it to the top news. As time decay is one of the major known factors of the Facebook news feed algorithm, it is safe to assume that there is a higher probability of making it into the top news the closer to “real time” the story is published. In fact, my experiment showed that, if a story was published within the last three hours, the chance of geting onto the top news was between 40 and 50%. In addition to selecting from the total number of updates generated by friends from the real-time stream, top news also displays its own tailored news stories that are not displayed in the most-recent feed. I call these stories “communication stories,” as they make a story out of two friends’ recent communicative interaction.19 Communication stories in Facebook typically take the form of “X commented on Y’s photo” or “X likes Y’s link.” Taking these tailored stories into the equation, a beter estimate for the 45/280 ratio would be a mere 12% chance of geting in the top news. Of all the 45 stories published, 17 were communication stories. What most of these 17 communication stories had in common was a high degree of interaction. For example, a typical story would say: “Anna commented on Claire’s photo” along with “11 people like this” and “View all 14 comments.” Not only does Facebook tailor specific stories for the top news feed, these stories also receive a significant amount of visibility as opposed to other types of edges. Presumably, the emphasis on quantification is supposed to simulate the impression of high activity in order to lower the threshold for participation on the platform.\n\nLife at the Top\n\n85","previous_page":84,"next_page":86}