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Sarcasm-GPT: advancing sarcasm detection with large language models
The Computer JournalAbstract Sarcasm detection is a nuanced challenge in natural language processing, requiring deep understanding of textual and contextual cues. We present Sarcasm-GPT, a large language model-based model that integrates four key components: prompt template generation, retrieval-augmented generation, chain-of-thought generation, and a ...
Qiuyu Li +4 more
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Exploiting Emojis for Sarcasm Detection
2019Modern social media platforms largely rely on text. However, the written text lacks the emotional cues of spoken and face-to-face dialogue, ambiguities are common, which is exacerbated in the short, informal nature of many social media posts. Sarcasm represents the nuanced form of language that individuals state the opposite of what is implied. Sarcasm
Jayashree Subramanian +3 more
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Literature survey of sarcasm detection
2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2017Sarcasm is a form of language in which individual convey their message in an implicit way i.e. the opposite of what is implied. Sarcasm detection is the task of predicting sarcasm in text. This is the crucial step in sentiment analysis due to inherently ambiguous nature of sarcasm. With this ambiguity, sarcasm detection has always been a difficult task,
Pranali Chaudhari, Chaitali Chandankhede
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Adversarial Training for Sarcasm Detection
2018Adversarial training has shown expressive performance in image classification task. However, there are few applications in natural language processing domain. In this paper, we propose to apply adversarial training strategy to sarcasm detection with small labeled samples.
Qinglin Zhang, Gangbao Chen, Di Chen
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Sarcasm Detection in Twitter Data
2019Posting sarcastic messages on social media like Twitter, Facebook, WhatsApp, etc., became a new trend to avoid direct negativity. Detecting this indirect negativity in the social media text has become an important task as they influence every business organization.
Santosh Kumar Bharti, Sathya Babu Korra
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Sarcasm Detection Using Contextual Incongruity
2018In the previous chapter, we presented approaches that capture incongruity within target text. However, as observed in errors reported by these approaches, some sarcastic text may require additional contextual information so that the sarcasm to be understood.
Aditya Joshi +2 more
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Sarcasm Detection in News Headlines
2022 6th International Conference on Computing Methodologies and Communication (ICCMC), 2022Karthik Sura +2 more
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Sarcasm Detection Using Deep Learning
2021 19th OITS International Conference on Information Technology (OCIT), 2021Deepak Sahoo +3 more
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MultiModal Sarcasm Detection: A Survey
2022 IEEE Delhi Section Conference (DELCON), 2022Aruna Bhat, Aditya Chauhan
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