A Survey of Sarcasm Detection Techniques in Natural Language Processing
Author:
Affiliation:
1. University of St. Thomas
2. GLA University Mathura,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10111836/10111935/10112176.pdf?arnumber=10112176
Reference50 articles.
1. Sarcasm Detection Using Multi-Head Attention Based Bidirectional LSTM
2. Sarcasm Detection Using Deep Learning With Contextual Features
3. Context-Based Feature Technique for Sarcasm Identification in Benchmark Datasets Using Deep Learning and BERT Model
4. The Significance of Global Vectors Representation in Sarcasm Analysis
5. Efficient Deep Learning Methods for Sarcasm Detection of News Headlines
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1. Harnessing heterogeneity: A multi-embedding ensemble approach for detecting fake news in Dravidian languages;Computers and Electrical Engineering;2024-12
2. Sarcasm Detection with BiLSTM Multihead Attention;2024 IEEE 9th International Conference for Convergence in Technology (I2CT);2024-04-05
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