{"id":186825,"date":"2011-09-28T00:00:00","date_gmt":"2011-09-30T06:23:23","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/modeling-conversations-in-social-media\/"},"modified":"2016-08-22T11:31:23","modified_gmt":"2016-08-22T18:31:23","slug":"modeling-conversations-in-social-media","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/modeling-conversations-in-social-media\/","title":{"rendered":"Modeling Conversations in Social Media"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Users of social media websites are engaging in public conversations at an unprecedented scale.  This massive corpus of naturally occurring, open-domain conversations presents new challenges and opportunities for data-driven conversation modeling.  In this talk I will describe work on automatically generating replies to open-domain Status Messages in Twitter.  In order to leverage millions of naturally occurring conversations, we adapt techniques from Statistical Machine Translation (SMT), to build a models capable of \u201ctranslating\u201d an arbitrary status message into an appropriate response.  Open-domain response generation could be useful for several applications including language generation in dialogue systems, and conversationally aware predictive text input.<br \/>\nIn addition I will describe work on unsupervised induction of dialogue acts in Twitter.  By remaining agnostic about the set of dialogue acts, we are able to learn a model which provides insight into the nature of communication in a new medium.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Users of social media websites are engaging in public conversations at an unprecedented scale. This massive corpus of naturally occurring, open-domain conversations presents new challenges and opportunities for data-driven conversation modeling. In this talk I will describe work on automatically generating replies to open-domain Status Messages in Twitter. In order to leverage millions of naturally [&hellip;]<\/p>\n","protected":false},"featured_media":196398,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_hide_image_in_river":0,"footnotes":""},"research-area":[],"msr-video-type":[],"msr-locale":[268875],"msr-post-option":[],"msr-session-type":[],"msr-impact-theme":[],"msr-pillar":[],"msr-episode":[],"msr-research-theme":[],"class_list":["post-186825","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/LHcGCr6VgEs","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/186825","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":0,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/186825\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/196398"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=186825"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=186825"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=186825"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=186825"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=186825"},{"taxonomy":"msr-session-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-session-type?post=186825"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=186825"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=186825"},{"taxonomy":"msr-episode","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-episode?post=186825"},{"taxonomy":"msr-research-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-theme?post=186825"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}