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...
Saved in:
Main Authors: | , , , , |
---|---|
Format: | Article |
Published: |
IEEE
2022
|
Online Access: | http://psasir.upm.edu.my/id/eprint/100800/ https://ieeexplore.ieee.org/document/9841563 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Putra Malaysia |