{"id":4702,"date":"2014-07-18T20:25:50","date_gmt":"2014-07-19T00:25:50","guid":{"rendered":"http:\/\/www.decisionsciencenews.com\/?p=4702"},"modified":"2014-07-18T20:25:50","modified_gmt":"2014-07-19T00:25:50","slug":"conference-digital-experimentation-2014-oct-10-11-2014-mit","status":"publish","type":"post","link":"https:\/\/www.decisionsciencenews.com\/?p=4702","title":{"rendered":"Conference on Digital Experimentation (CODE), Oct 10-11, 2014 at MIT"},"content":{"rendered":"<p>ABSTRACT SUBMISSION DEADLINE AUGUST 15 2014<\/p>\n<p style=\"text-align: center;\">\n<a href=\"http:\/\/www.decisionsciencenews.com\/wp-content\/uploads\/2014\/07\/code.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-4703\" src=\"http:\/\/www.decisionsciencenews.com\/wp-content\/uploads\/2014\/07\/code.png\" alt=\"code\" width=\"488\" height=\"207\" \/><\/a>\n<\/p>\n<p><strong><a href=\"http:\/\/codecon.net\/\">Conference on Digital Experimentation (CODE) 2014<\/a><\/strong><\/p>\n<p><strong>About<\/strong><br \/>\nThe ability to rapidly deploy micro-level randomized experiments at population scale is, in our view, one of the most significant innovations in modern social science. As more and more social interactions, behaviors, decisions, opinions and transactions are digitized and mediated by online platforms, we can quickly answer nuanced causal questions about the role of social behavior in population-level outcomes such as health, voting, political mobilization, consumer demand, information sharing, product rating and opinion aggregation. When appropriately theorized and rigorously applied, randomized experiments are the gold standard of causal inference and a cornerstone of effective policy. But the scale and complexity of these experiments also create scientific and statistical challenges for design and inference. The purpose of the Conference on Digital Experimentation at MIT (CODE) is to bring together leading researchers conducting and analyzing large scale randomized experiments in digitally mediated social and economic environments, in various scientific disciplines including economics, computer science and sociology, in order to lay the foundation for ongoing relationships and to build a lasting multidisciplinary research community.<\/p>\n<p><strong>Speakers<\/strong><br \/>\nEric Anderson, Kellogg<br \/>\nAlessandro Aquisti, CMU<br \/>\nSusan Athey, Stanford<br \/>\nEric Horvitz, Microsoft<br \/>\nJeremy Howard, Khosla Ventures<br \/>\nRon Kohavi, Microsoft<br \/>\nKarim R. Lakhani, Harvard<br \/>\nJohn Langford, Microsoft<br \/>\nDavid Lazer, Northeastern<br \/>\nSendhil Mullainathan, Harvard<br \/>\nClaudia Perlich, Distillery<br \/>\nDavid Reiley, Google<br \/>\nHal Varian, Google<br \/>\nDan Wagner, Civis<br \/>\nDuncan Watts, Microsoft<\/p>\n<p><strong>Important Dates<\/strong><br \/>\nWorkshop: October 10-11, 2014<br \/>\nAbstract Submission Deadline: August 15, 2014<br \/>\nNotification to Authors: September 1, 2014<br \/>\nFinal Abstract Submission: September 12, 2014<br \/>\nEarly Registration Deadline: September 19, 2014<br \/>\nOnsite Registration: October 10, 2014<\/p>\n","protected":false},"excerpt":{"rendered":"<p> The purpose of the Conference on Digital Experimentation at MIT (CODE) is to bring together leading researchers conducting and analyzing large scale randomized experiments in digitally mediated social and economic environments, in various scientific disciplines including economics, computer science and sociology, in order to lay the foundation for ongoing relationships and to build a lasting multidisciplinary research community.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[3],"tags":[649,903,902,899,290,17,897,27,898,901,542,904,900,138],"class_list":["post-4702","post","type-post","status-publish","format-standard","hentry","category-conferences","tag-649","tag-boston","tag-cambridge","tag-code","tag-computer-science","tag-conference","tag-digital","tag-economics","tag-experimentation","tag-machine-learning","tag-mit","tag-october","tag-randomized","tag-sociology"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p4LKj-1dQ","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/4702","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=4702"}],"version-history":[{"count":4,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/4702\/revisions"}],"predecessor-version":[{"id":4707,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/4702\/revisions\/4707"}],"wp:attachment":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4702"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4702"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4702"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}