Results 31 to 40 of about 2,787,876 (276)
A Comprehensive Survey on Arabic Sarcasm Detection: Approaches, Challenges and Future Trends
IEEE Access, 2023 On social media platforms, it is essential to express one’s thoughts, opinions, and reviews. One of the most widely used linguistic forms to criticize or express a person’s ideas with ridicule is sarcasm, where the written text has both ...
Alaa Rahma +2 more
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Sarcasm detection on Twitter [PDF]
, 2016 State-of-the-art approaches for sarcasm detection in social media combine lexical clues with contextual information surrounding the potentially sarcastic posting including author information.
Lyu, Hao
core +3 more sources
Heliyon, 2023 Sarcasm detection research in Bengali is still limited due to a lack of relevant resources. In this context, getting high-quality annotated data is costly and time-consuming. Therefore, in this paper, we present a transformer-based generative adversarial
Sanzana Karim Lora +4 more
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Detecting sarcasm in multi-domain datasets using convolutional neural networks and long short term memory network model [PDF]
PeerJ Computer Science, 2021 Sarcasm emerges as a common phenomenon across social networking sites because people express their negative thoughts, hatred and opinions using positive vocabulary which makes it a challenging task to detect sarcasm.
Ramish Jamil +5 more
doaj +2 more sources
Sarcasm Detection: A Comparative Study
CoRR, 2021 Sarcasm detection is the task of identifying irony containing utterances in sentiment-bearing text. However, the figurative and creative nature of sarcasm poses a great challenge for affective computing systems performing sentiment analysis. This article compiles and reviews the salient work in the literature of automatic sarcasm detection.
Hamed Yaghoobian +2 more
openaire +3 more sources
Sarcasm detection of tweets without #sarcasm: data science approach [PDF]
, 2021 Identifying sarcasm present in the text could be a challenging work. In sarcasm, a negative word can flip the polarity of a positive sentence. Sentences can be classified as sarcastic or non-sarcastic.
Bagate, Rupali Amit, Suguna, R.
core +2 more sources
Unfolding Sarcasm in Twitter Using C-RNN Approach
, 2021 Sarcasm detection in text is an inspiring field to explore due to its contradictory behavior. Textual data can be analyzed in order to discover clues those lead to sarcasm.
Akash Mehta, Dutta, Shawni
core +1 more source
Sarcasm Detection Using an Ensemble Approach [PDF]
Proceedings of the Second Workshop on Figurative Language Processing, 2020 We present an ensemble approach for the detection of sarcasm in Reddit and Twitter responses in the context of The Second Workshop on Figurative Language Processing held in conjunction with ACL 2020(1). The ensemble is trained on the predicted sarcasm probabilities of four component models and on additional features, such as the sentiment of the ...
Jens Lemmens +4 more
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FiLMing Multimodal Sarcasm Detection with Attention [PDF]
, 2021 Sarcasm detection identifies natural language expressions whose intended meaning is different from what is implied by its surface meaning. It finds applications in many NLP tasks such as opinion mining, sentiment analysis, etc. Today, social media has given rise to an abundant amount of multimodal data where users express their opinions through text ...
Sundesh Gupta +4 more
openaire +3 more sources
Unveiling Sarcastic Intent: Web-Based Detection of Sarcasm In News Headlines
Journal of Computing Research and Innovation, 2023 Detecting sarcasm in news headlines poses a significant challenge due to the intricate nature of language and the subtle nuances of sarcastic expressions. This study uses machine learning techniques to introduce a novel web-based sarcasm detection system
Mohd Nazzim Lahaji +2 more
doaj +1 more source