{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/soc2seq-social-embedding-meets-conversation","title":"soc2seq: Social Embedding meets Conversation Model","arxiv_id":"1702.05512","date":"2017-02-17","proceeding":null,"authors":["Parminder Bhatia","Marsal Gavalda","Arash Einolghozati"],"abstract":"While liking or upvoting a post on a mobile app is easy to do, replying with\na written note is much more difficult, due to both the cognitive load of coming\nup with a meaningful response as well as the mechanics of entering the text.\nHere we present a novel textual reply generation model that goes beyond the\ncurrent auto-reply and predictive text entry models by taking into account the\ncontent preferences of the user, the idiosyncrasies of their conversational\nstyle, and even the structure of their social graph. Specifically, we have\ndeveloped two types of models for personalized user interactions: a\ncontent-based conversation model, which makes use of location together with\nuser information, and a social-graph-based conversation model, which combines\ncontent-based conversation models with social graphs.","url_abs":"http://arxiv.org/abs/1702.05512v3","url_pdf":"http://arxiv.org/pdf/1702.05512v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"soc2seq-social-embedding-meets-conversation","repo_url":"https://github.com/pbhatia243/Neural_Conversation_Models","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"model","task_name":"model"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}