{"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":105,"pdf_page":115,"physical_index":115,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"9ba82a6a8bcc897bb6423b60c5a0be2e0b0b53ac687c079e85ed262eb6463d16"},"chapter":"IF...THEN","content":"E N T E R T H E P O P U L A R I T Y C O N T E S T\n\nWhile algorithms might be bad at judging human complexity and emotional valences, they also seem to augment and amplify traditional social norms and hierarchies. For participants, this is most evident in terms of the perceived capacity of algorithms to filter and sort content and people according to their popularity and importance. Algorithms, of course, are not unique in this respect. The media have always operated according to the principle of privileging certain voices and personalities over others. As Altheide and Snow (1979) atested in their influential account of media logic, the mass media fundamentally work by assigning some expressions more weight and importance than others. The logic of popularity is highly evident in the operational logics of social media platforms, which often incorporate some form of personalized ranking mechanism to distinguish popular content from less important items (van Dijck & Poell, 2013). Technically, however, popularity and personalization are not easily squared (Amatriain,  2013). Whereas popularity is generally about recommending items according to a global notion of relevance, personalization is about satisfying members with varying tastes. As Amatriain writes in a paper explicating the models behind Netflix recommendations, the goal “becomes to find a personalized ranking function that is beter than item popularity” in order to cater to a variety of tastes (2013: 3). This goal does not just apply to Netflix but to prety much every platform that seeks to filter and rank its content to retain user atention in some way or another.\n\nIndeed, the balancing act between quantity and quality, between high degrees of links/likes and individual practical engagement, constitutes a core challenge for platforms. When the balancing act fails—as it often does—users notice. Why, for example, did Netflix recommend a horror movie when Katy only ever watches romantic comedies, or why does OKCupid’s matching algorithm only seem to suggest outdoorsy types when all Robin wants to do is go to concerts and eat good food? Just because many people like horror movies or because the fit and healthy seem to be a thing on dating apps, this does not mean either is right for everyone. People particularly notice the popularity contest in terms of the ways in which social media platforms such as Facebook have a tendency to make the same people or the same type of content visible time and again. Lucas, a 25-year-old quality assurance engineer, says he spends a lot of his spare time on social media. Lately, he has noticed that there is absolutely no new content popping up on his Facebook feed.\n\nAffective Landscapes\n\n105","previous_page":104,"next_page":106}