Multi-feature fusion framework for sarcasm identification on twitter data: A machine learning based approach.
Sarcasm is the main reason behind the faulty classification of tweets. It brings a challenge in natural language processing (NLP) as it hampers the method of finding people's actual sentiment. Various feature engineering techniques are being investigated for the automatic detection of sarcasm....
Guardado en:
Autores principales: | Christopher Ifeanyi Eke, Azah Anir Norman, Liyana Shuib |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/4fad5568908a48ac807c253124429372 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Hyperbolic Feature-based Sarcasm Detection in Telugu Conversation Sentences
por: Bharti Santosh Kumar, et al.
Publicado: (2020) -
The twittering machine : (La máquina de trinar) /
por: Seymour, Richard
Publicado: (2020) -
Breast Cancer Detection via Global and Local Features using Digital Histology Images
por: Ghulam Murtaza, et al.
Publicado: (2021) -
Controversy over the Concept of Irony (=Al-Mophareqeh) from Sarcasm to Contradiction; A Linguistic and Semantic Approach
por: Ali Andalib, et al.
Publicado: (2019) -
KK-DBP: A Multi-Feature Fusion Method for DNA-Binding Protein Identification Based on Random Forest
por: Yuran Jia, et al.
Publicado: (2021)