{"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":98,"pdf_page":108,"physical_index":108,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"52e4edde94e28c012ff27d3f40f30f43b6b2482ebe5a84810fe0fd9e15ae9dca"},"chapter":"IF...THEN","content":"From a phenomenological perspective, what is of interest is how the seemingly hidden and unfamiliar technological processes permit or limit people’s movements and whereabouts. For people in their everyday lives, what maters is not necessarily the truth (whatever that is) but “practical knowing” (Thrift,  2007: 121); that is, people “know as they go, as they journey through the world along paths of travel” (Ingold, 2011: 154). In other words, people learn what they need to know in order to engage meaningfully with and find their way around an algorithmically mediated world. For Michael, for example, Facebook’s news feed algorithm feels like a gatekeeper that stands in the way of his music career. Knowing the algorithm just enough to ensure that his followers receive his updates maters to him—not just personally but also professionally. The kind of knowledge that I am concerned with here, then, treats the beliefs people form about algorithms not as right or wrong but as a point of access for understanding how and when algorithms mater.\n\nResearching Personal Algorithm Stories\n\nContrary to the notion that “the individual user is incapable of really experiencing the efect that algorithms have in determining one’s life as algorithms rarely, if ever, speak to the individual” (Cheney-Lippold, 2011: 176), I suggest in this chapter that people do experience algorithms; and, while algorithms might not speak directly to individuals, they might speak through them. Here, I report on a series of personal algorithm stories, that is, stories about algorithms derived from people’s online experiences. Over a two-year period from October 2014 to August 2016, I collected personal algorithm stories from social media users through email and face-to-face interviews with 35 individuals about their perceptions and awareness of algorithms. The data set also contains over 2000 tweets writen by social media users that contain popular hashtags such as #RIPTwiter and #InstagramAlgorithm as well as blog posts and archived comment sections of newspaper articles discussing algorithms. Taking my lead from Zizi Papacharissi (2015), who sees the collective discourses organized around hashtags on Twiter as indicative of an emergent structure of feeling, I shall expand this notion to include not just hashtags but also disparate tweets about algorithms as indicative of an afective landscape surrounding the felt presence of algorithms. Going back to Michael and Rachel, their algorithm stories were originally collected using their own tweets as a starting point. Expressing feelings of bewilderment and defeat, their tweets simply read: “This Facebook algorithm is just super frustrating” (Michael) and “Facebook algorithm destroys friendships” (Rachel).13 Seeing these kinds of uterances as part of my Twiter feed, I could not help wondering where they came from. What had prompted Michael and Rachel to tweet those things?\n\nMethodologically, I engage in what might be called a scenographic inquiry into the afective landscapes generated in and through algorithms by atending to the scenes, situations, episodes, and interruptions that give rise to the felt presence of algorithms in everyday life. By “scenographic,” I mean a methodological sensibility akin to writers and scholars such as Lauren Berlant and Kathleen Stewart, both of whom atend to cases or scenes of the ordinary as a way of making afective processes more palpable. For Stewart (2007), scenes are method and genre, a way of writing about ordinary afects as a series of happenings that, taken together, form a story about what it feels like to live in contemporary America. As McCormack writes, the scene or situation “becomes a way of gathering the sense of worlds that mater while also posing the question of how the force of these worlds might become part of their stories” (2015: 93). A situation, as Berlant defines it, “is a state of things in which something that will perhaps mater is unfolding amid the usual activity of life. It is a state of animated and animating suspension,” one “that forces itself on consciousness, that produces a sense of the emergence of something in the present” (2011: 5). Algorithms, I suggest, may be productive of such emerging presences and “accessed” via the ways in which they make people feel and the stories that they tell about those encounters. This is closely related to the notion of afect but not exactly the same. As Papacharissi (2015) points out, afect is what permits feelings to be felt, it is the movement that may lead to a particular feeling. Afect, she suggests, can be thought of as the “rhythm of our pace as we walk” (2015: 21). For example, a fast-paced rhythm may lead to and amplify feelings of stress; a slow and light-paced rhythm may make us calm. In the context of this study, the question is how we might think of the force of movement that algorithms create, and how it prompts a “reason to react,” as Stewart puts it (2007: 16).\n\n98\n\nIF . . . THEN","previous_page":97,"next_page":99}