{"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/a-factored-neural-network-model-for","title":"A Factored Neural Network Model for Characterizing Online Discussions in Vector Space","arxiv_id":null,"date":"2017-09-01","proceeding":"EMNLP 2017 9","authors":["Hao Cheng","Hao Fang","Mari Ostendorf"],"abstract":"We develop a novel factored neural model that learns comment embeddings in an unsupervised way leveraging the structure of distributional context in online discussion forums. The model links different context with related language factors in the embedding space, providing a way to interpret the factored embeddings. Evaluated on a community endorsement prediction task using a large collection of topic-varying Reddit discussions, the factored embeddings consistently achieve improvement over other text representations. Qualitative analysis shows that the model captures community style and topic, as well as response trigger patterns.","url_abs":"https://aclanthology.org/D17-1243","url_pdf":"https://aclanthology.org/D17-1243.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":"a-factored-neural-network-model-for","repo_url":"https://github.com/hao-cheng/factored_neural","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"feature-engineering","task_name":"Feature Engineering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}