{"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/the-role-of-conversation-context-for-sarcasm","title":"The Role of Conversation Context for Sarcasm Detection in Online Interactions","arxiv_id":"1707.06226","date":"2017-07-19","proceeding":"WS 2017 8","authors":["Debanjan Ghosh","Alexander Richard Fabbri","Smaranda Muresan"],"abstract":"Computational models for sarcasm detection have often relied on the content\nof utterances in isolation. However, speaker's sarcastic intent is not always\nobvious without additional context. Focusing on social media discussions, we\ninvestigate two issues: (1) does modeling of conversation context help in\nsarcasm detection and (2) can we understand what part of conversation context\ntriggered the sarcastic reply. To address the first issue, we investigate\nseveral types of Long Short-Term Memory (LSTM) networks that can model both the\nconversation context and the sarcastic response. We show that the conditional\nLSTM network (Rocktaschel et al., 2015) and LSTM networks with sentence level\nattention on context and response outperform the LSTM model that reads only the\nresponse. To address the second issue, we present a qualitative analysis of\nattention weights produced by the LSTM models with attention and discuss the\nresults compared with human performance on the task.","url_abs":"http://arxiv.org/abs/1707.06226v1","url_pdf":"http://arxiv.org/pdf/1707.06226v1.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":"the-role-of-conversation-context-for-sarcasm","repo_url":"https://github.com/debanjanghosh/sarcasm_context","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"the-role-of-conversation-context-for-sarcasm","repo_url":"https://github.com/Alex-Fabbri/deep_learning_nlp_sarcasm","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"sarcasm-detection","task_name":"Sarcasm Detection"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1707.06226","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}