{"id":215438,"date":"2016-06-01T00:00:00","date_gmt":"2016-06-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/trendingistrending-when-algorithms-become-culture-3\/"},"modified":"2021-05-28T15:03:21","modified_gmt":"2021-05-28T22:03:21","slug":"trendingistrending-when-algorithms-become-culture-3","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/trendingistrending-when-algorithms-become-culture-3\/","title":{"rendered":"#Trendingistrending: When Algorithms Become Culture"},"content":{"rendered":"<div class=\"asset-content\">\n<div class=\"asset-content\">\n<p>Algorithms may now be our most\u00a0important knowledge technologies, &#8220;the scientific instruments of a society\u00a0at large,&#8221; and they are increasingly vital to how we organize human social\u00a0interaction, produce authoritative knowledge, and choreograph our participation\u00a0in public life. Search engines, recommendation systems, and edge algorithms on\u00a0social networking sites: these not only help us find information, they provide\u00a0a means to know what there is to know and to participate in social and\u00a0political discourse.<\/p>\n<p>If not as pervasive and\u00a0structurally central as search and recommendation, <em>trending<\/em> has emerged\u00a0as an increasingly common feature of such interfaces and seems to be growing in\u00a0cultural importance. It represents a fundamentally different logic for how to\u00a0algorithmically navigate social media: besides identifying and highlighting\u00a0what might be relevant to &#8220;you&#8221; specifically, trending algorithms\u00a0identify what is popular with &#8220;us&#8221; more broadly.<\/p>\n<p>But while the techniques may be\u00a0new, the instinct is not: what today might be identified as\u00a0&#8220;trending&#8221; is the latest instantiation of the instinct to map public\u00a0attention and interest, be it surveys and polling, audience metrics, market\u00a0research, forecasting, and trendspotting. Understanding the calculations and\u00a0motivations behind the production of these &#8220;calculated publics,&#8221;in\u00a0this historical context, helps highlight how these algorithms are relevant to\u00a0our collective efforts to know and be known.<\/p>\n<p>Rather than discuss the effect of\u00a0trending algorithms, I want to ask what it means that they have become a\u00a0meaningful element of public culture. Algorithms, particularly those involved in\u00a0the movement of culture, are both mechanisms of distribution and\u00a0valuation, part of the process by which knowledge institutions circulate and\u00a0evaluate information, the process by which new media industries provide and\u00a0sort culture. This essay examines the way these algorithmic techniques\u00a0themselves become cultural objects, get taken up in our thinking about culture\u00a0and the public to which it is addressed, and get contested both for what they\u00a0do and what they reveal. We should ask not just how algorithms shape culture,\u00a0but how they become culture.<\/p>\n<\/div>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Algorithms may now be our most\u00a0important knowledge technologies, &#8220;the scientific instruments of a society\u00a0at large,&#8221; and they are increasingly vital to how we organize human social\u00a0interaction, produce authoritative knowledge, and choreograph our participation\u00a0in public life. Search engines, recommendation systems, and edge algorithms on\u00a0social networking sites: these not only help us find information, they provide\u00a0a means [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13561,13559],"msr-publication-type":[193721],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-215438","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-algorithms","msr-research-area-social-sciences","msr-locale-en_us"],"msr_publishername":"Routledge","msr_edition":"","msr_affiliation":"","msr_published_date":"2016-6-1","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"Algorithmic Cultures: Essays on Meaning, Performance and New Technologies","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":0,"msr_main_download":"","msr_publicationurl":"http:\/\/culturedigitally.org\/2016\/02\/trendingistrending\/","msr_doi":"","msr_publication_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"http:\/\/culturedigitally.org\/2016\/02\/trendingistrending\/","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":0,"url":"http:\/\/culturedigitally.org\/2016\/02\/trendingistrending\/"}],"msr-author-ordering":[{"type":"user_nicename","value":"Tarleton Gillespie","user_id":33877,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Tarleton Gillespie"}],"msr_impact_theme":[],"msr_research_lab":[199563],"msr_event":[],"msr_group":[332906],"msr_project":[170498],"publication":[],"video":[],"download":[],"msr_publication_type":"inbook","related_content":{"projects":[{"ID":170498,"post_title":"Social Media Collective","post_name":"social-media-collective","post_type":"msr-project","post_date":"2010-07-06 19:46:44","post_modified":"2023-04-14 15:38:19","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/social-media-collective\/","post_excerpt":"The mission of the SMC is first and foremost\u00a0to bring critical and analytical lenses to contemporary sociotechnical systems, particularly around media, expertise, labor, and publics. We aim to contribute to the academic fields concerned with the sociological dimensions of new media and new forms of work. We also aim to insist that these questions be part of the broader research agenda of MSR and the efforts of the company. But our mission is also in&hellip;","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170498"}]}}]},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/215438","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/215438\/revisions"}],"predecessor-version":[{"id":412631,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/215438\/revisions\/412631"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=215438"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=215438"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=215438"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=215438"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=215438"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=215438"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=215438"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=215438"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=215438"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=215438"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=215438"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=215438"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=215438"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=215438"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=215438"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=215438"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}