{"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":198,"pdf_page":208,"physical_index":208,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"39b952ebbadd1e4ee5aa72394ebfa74406fff580567b37b4ed27af5e4e3affe4"},"chapter":"IF...THEN","content":"McCormack, Derek P., 99–100   \nMcGoey, Linsey, 56–57   \nmachine-learning algorithms, 20, 23–28, 32, 35–36, 53, 95, 97, 116, 156, 157 deep learning, 25, 27 facial recognition, 26–27 feature extraction, 25 models, 24–25 problematic results, 27–28 strategic unknowns, as, 56–58 supervised/semi-supervised learning, 24, 25–26   \nMackenzie, Adrian, 14, 24, 26, 29, 30, 61, 67, 68, 87, 88, 90, 142   \n“making up people,” 9–10, 32   \nmaterial-discursive practices, 120, 125, 126, 147, 151   \nmateriality, 8, 17, 30, 68, 69, 72, 90, 120, 121, 125, 158 see also relational materialism; sociomateriality   \nmatering, 18, 55, 120–21, 122, 125, 146, 147   \nmedia, 1, 29 see also algorithmic power and politics; news media; social media   \nmedia studies, 15, 68   \nmemories, 103–4   \nMenlo Park (Facebook HQ), 70   \nmental models, 96–97, 115   \nmethodological tactics, 15, 16, 42, 59–64, 151   \nMeyer, Philip, Precision Journalism, 122, 123   \nMichael, Mike, 49, 58   \nmicropolitics, 94, 116   \nMicrosoft, 152   \nmisidentifications, 102–3, 115   \nMol, Annemarie, 3, 15–16, 19, 39, 49, 56, 121, 151   \nMoses, Robert, 23, 35   \nmultiplicity of algorithms, 19–20, 27, 39, 42, 48 power of algorithms, 32–38 see also algorithmic power and politics social concerns, 29–32 targeting the algorithm, 38–40   \nmusic-streaming, 54\n\nnaive Bayes classifier, 26, 61   \nNarrative Science, 124   \nNaughton, John, 52–53   \nnearest neighbour algorithm, 27   \nnegative knowledge, 46–47, 59   \nNetflix, 2, 31, 47, 48, 62, 99, 108\n\nrecommender system, 47–48, 105\n\n“taggers,” 53\n\nneural networks, 27, 59\n\nNew York Times, 53, 70, 77\n\nnews feed algorithms, 2, 3, 72–74 see also Facebook news feed\n\nnews media, 6, 17–18, 55, 114, 118, 120–24, 150, 158 see also fake news; journalism; Scandinavian news media computerization and digitization, 120, 122–24\n\nnewsworthiness, 26, 53\n\nnonknowledge, 46, 47, 61–62\n\nNorwegian news media, 124, 125, 131, 133, 138 see also Aftenposten; Scandinavian news media\n\nOKCupid, 105 OKCupid, 105\n\nOmni, 18, 125, 133–34, 136–38, 139, 140, 145–46   \nontological politics, 3, 16, 18, 39–40, 56, 120, 146, 148, 151, 157–58   \nontology of software see under software   \noperational logics, 12, 17, 21, 60–61, 63, 105, 109, 110, 112, 113, 144 Facebook algorithm, 77, 92   \nOremus, Will, 48, 53, 78   \norientations, 3, 8, 31, 127, 154–57   \npage generation algorithm, 47–48   \nPageRank, 39   \nPanopticon, 74, 82–84, 85, 92   \nPapacharissi, Zizi, 98, 99, 115   \nparticipatory subjectivity, 17, 88–90, 92, 155   \nPasquale, Frank, The Black Box Society, 29, 34–35, 41–42, 45   \npatern recognition, 25, 57   \nperformativity, 1, 4, 28, 31, 38, 50   \npersonal algorithm stories see encounters with algorithms   \npersonalization, 47, 105, 108–9, 127, 128, 129 see also under journalism   \npersonalized video ranker (PVR), 47   \npharmacological objects, 146   \nphenomenological approach, 61–63, 151   \nplagiarism algorithms, 37   \nplayful learning, 62, 112–13   \nPolaris Media, 125, 128, 140   \npolitics, 3, 67 see also algorithmic power and politics; ontological politics   \nPolitiken, 125, 131, 139, 143   \npopularity, 2, 89–90, 100, 105–9   \npost-ANT, 49   \npost-truth, 118, 147   \npower, 16, 72–73, 153, 155 see also algorithmic power and politics; disciplinary power concepts of, 33, 116–17 see also under Foucault, Michel\n\n198\n\nIndex","previous_page":197,"next_page":199}