Context-driven satire detection with deep learning

This work discuss the task of automatically detecting satire instances in short articles. It is the study of extracting the most optimal features by using a deep learning architecture combined with carefully handcrafted contextual features. It is found that a few sets can perform well when they are...

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Bibliographic Details
Main Authors: Razali, Md Saifullah, Abdul Halin, Alfian, Chow, Yang-Wai, Mohd Norowi, Noris, Doraisamy, Shyamala
Format: Article
Published: IEEE 2022
Online Access:http://psasir.upm.edu.my/id/eprint/100800/
https://ieeexplore.ieee.org/document/9841563
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Institution: Universiti Putra Malaysia

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