{"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/modelling-context-with-user-embeddings-for","title":"Modelling Context with User Embeddings for Sarcasm Detection in Social Media","arxiv_id":"1607.00976","date":"2016-07-04","proceeding":"CONLL 2016 8","authors":["Silvio Amir","Byron C. Wallace","Hao Lyu","Paula Carvalho Mário J. Silva"],"abstract":"We introduce a deep neural network for automated sarcasm detection. Recent\nwork has emphasized the need for models to capitalize on contextual features,\nbeyond lexical and syntactic cues present in utterances. For example, different\nspeakers will tend to employ sarcasm regarding different subjects and, thus,\nsarcasm detection models ought to encode such speaker information. Current\nmethods have achieved this by way of laborious feature engineering. By\ncontrast, we propose to automatically learn and then exploit user embeddings,\nto be used in concert with lexical signals to recognize sarcasm. Our approach\ndoes not require elaborate feature engineering (and concomitant data scraping);\nfitting user embeddings requires only the text from their previous posts. The\nexperimental results show that our model outperforms a state-of-the-art\napproach leveraging an extensive set of carefully crafted features.","url_abs":"http://arxiv.org/abs/1607.00976v2","url_pdf":"http://arxiv.org/pdf/1607.00976v2.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":"modelling-context-with-user-embeddings-for","repo_url":"https://github.com/samiroid/CUE-CNN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"modelling-context-with-user-embeddings-for","repo_url":"https://github.com/rishabhmisra/Sarcasm-Detection-using-CNN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"modelling-context-with-user-embeddings-for","repo_url":"https://github.com/rishabhmisra/Sarcasm-Detection-using-NN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"feature-engineering","task_name":"Feature Engineering"},{"task_slug":"sarcasm-detection","task_name":"Sarcasm Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1607.00976","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}