{"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/what-you-say-and-how-you-say-it-joint","title":"What You Say and How You Say it: Joint Modeling of Topics and Discourse in Microblog Conversations","arxiv_id":"1903.07319","date":"2019-03-18","proceeding":"TACL 2019 3","authors":["Jichuan Zeng","Jing Li","Yulan He","Cuiyun Gao","Michael R. Lyu","Irwin King"],"abstract":"This paper presents an unsupervised framework for jointly modeling topic\ncontent and discourse behavior in microblog conversations. Concretely, we\npropose a neural model to discover word clusters indicating what a conversation\nconcerns (i.e., topics) and those reflecting how participants voice their\nopinions (i.e., discourse). Extensive experiments show that our model can yield\nboth coherent topics and meaningful discourse behavior. Further study shows\nthat our topic and discourse representations can benefit the classification of\nmicroblog messages, especially when they are jointly trained with the\nclassifier.","url_abs":"http://arxiv.org/abs/1903.07319v1","url_pdf":"http://arxiv.org/pdf/1903.07319v1.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":"what-you-say-and-how-you-say-it-joint","repo_url":"https://github.com/zengjichuan/Topic_Disc","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[{"slug":"twt-16","name":"TWT-16","full_name":null}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1903.07319","atlas_url":"https://app.syntology.ai/?focus=1903.07319","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}