Results 31 to 40 of about 13,126 (249)

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, Hongfei Lin, Liang Yang, Xiaochao Fan, Yonghe Chu, Kan Xu, Di Wu   +6 more
doaj   +1 more source

Research on Sarcastic Emotion Recognition Based on Multiple Feature Fusion [PDF]

ITM Web of Conferences
Sarcasm detection significantly enhances the performance of various natural language processing applications, such as sentiment analysis, opinion mining, and stance detection.
Si Kaihao
doaj   +1 more source

EFAFN: An Efficient Feature Adaptive Fusion Network with Facial Feature for Multimodal Sarcasm Detection

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, Hangming Zhang, Shengjiao Yang, Jianming Wang   +3 more
doaj   +1 more source

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, Fuqiang Lin, Xuan Zhang, Guowei Li, Bo Liu   +4 more
doaj   +1 more source

LT3: sentiment analysis of figurative tweets: piece of cake #NotReally [PDF]

, 2015
This paper describes our contribution to the SemEval-2015 Task 11 on sentiment analysis of figurative language in Twitter. We considered two approaches, classification and regression, to provide fine-grained sentiment scores for a set of tweets that are ...
Hoste, Veronique, Lefever, Els, Van Hee, Cynthia   +2 more
core   +2 more sources

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
doaj   +1 more source

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, María García-Gámez   +1 more
doaj   +1 more source

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., Davidov D., Frome A., Ghosh D., Gibbs R., González-Ibánez R., Kincaid J. P., Mikolov T., Riloff E., Tepperman J., Tsur O., Veale T., Verstraten P., Wang Z., You Q.   +14 more
core   +1 more source

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, Alfian Abdul Halin, Yang-Wai Chow, Noris Mohd Norowi, Shyamala Doraisamy   +4 more
openaire   +2 more sources

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, Carman, Mark, Joshi, Aditya, Patel, Kevin, Tripathi, Vaibhav   +4 more
core   +1 more source