Results 31 to 40 of about 13,254 (269)
A Multi-Dimension Question Answering Network for Sarcasm Detection
IEEE Access, 2020 Sarcasm is a form of figurative language where the literal meaning of words cannot hold, and instead the opposite interpretation is intended in a text.
Yufeng Diao +6 more
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Research on Sarcastic Emotion Recognition Based on Multiple Feature Fusion [PDF]
ITM Web of ConferencesSarcasm detection significantly enhances the performance of various natural language processing applications, such as sentiment analysis, opinion mining, and stance detection.
Si Kaihao
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Applied Sciences, 2022 Sarcasm often manifests itself in some implicit language and exaggerated expressions. For instance, an elongated word, a sarcastic phrase, or a change of tone. Most research on sarcasm detection has recently been based on text and image information.
Yukuan Sun +3 more
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Jointly Learning Sentimental Clues and Context Incongruity for Sarcasm Detection
IEEE Access, 2022 Sarcasm is widely used in social communities and e-commerce platforms, failing to detect it in natural language processing tasks leads to false positives, e.g., opinion mining and sentiment classification.
Wangqun Chen +4 more
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Sarcasm Over Time and Across Platforms: Does the Way We Express Sarcasm Change?
IEEE Access, 2022 Sarcasm is a sophisticated form of speech used to convey a message other than the apparent one. To date, there are numerous papers that have discussed the idea of automatic sarcasm detection and how it could be used for sentiment analysis improvement ...
Mondher Bouazizi, Tomoaki Ohtsuki
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Corpus Annotation and Analysis of Sarcasm in Twitter: #CatsMovie vs. #TheRiseOfSkywalker
Atlantis, 2022 Sentiment analysis is a natural language processing task that has received increased attention in the last decade due to the vast amount of opinionated data on social media platforms such as Twitter.
Antonio Moreno-Ortiz +1 more
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Sarcasm Relation to Time: Sarcasm Detection with Temporal Features and Deep Learning
, 2022 Abstract This paper discusses a framework used to detect sarcasm in relation to time. It uses a set of deep learning extracted features (deep features) combined with a set of handcrafted features. The results of the experiments are positive in terms of Accuracy, Precision, Recall and F1-measure. The combination of features is classified using a
Md Saifullah Razali +4 more
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Detecting Sarcasm in Multimodal Social Platforms
, 2016 Sarcasm is a peculiar form of sentiment expression, where the surface sentiment differs from the implied sentiment. The detection of sarcasm in social media platforms has been applied in the past mainly to textual utterances where lexical indicators ...
Bamman D. +14 more
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Contextualized Sarcasm Detection on Twitter
Proceedings of the International AAAI Conference on Web and Social Media, 2021 Sarcasm requires some shared knowledge between speaker and audience; it is a profoundly contextual phenomenon. Most computational approaches to sarcasm detection, however, treat it as a purely linguistic matter, using information such as lexical cues and their corresponding sentiment as predictive features.
David Bamman, Noah Smith
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Are Word Embedding-based Features Useful for Sarcasm Detection?
, 2016 This paper makes a simple increment to state-of-the-art in sarcasm detection research. Existing approaches are unable to capture subtle forms of context incongruity which lies at the heart of sarcasm.
Bhattacharyya, Pushpak +4 more
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