Improving Hate Speech Detection Using Double-Layers Hybrid CNN-RNN Model on Imbalanced Dataset
Hate speech detection is crucial in curbing online toxicity and fostering a safer digital environment. Previous research has proposed the use of a hybrid CNN-RNN model for this purpose. This study aims to improve the performance of the hybrid CNN-RNN method by using a double-layer approach to addres...
Published in: | IEEE ACCESS |
---|---|
Main Authors: | Riyadi, Slamet; Andriyani, Annisa Divayu; Sulaiman, Siti Noraini |
Format: | Article |
Language: | English |
Published: |
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
2024
|
Subjects: | |
Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001349751700001 |
Similar Items
-
Digital hate speech and othering: The construction of hate speech from Malaysian perspectives
by: Zamri N.A.K.; Mohamad Nasir N.A.; Hassim M.N.; Ramli S.M.
Published: (2023) -
Evaluating aspect-based sentiment classification on Twitter hate speech using neural networks and word embedding features
by: Zainuddin N.; Selamat A.; Ibrahim R.
Published: (2018) -
CW Radar Based Silent Speech Interface Using CNN
by: Mohd Shariff K.K.; Nadiah Yusni A.; Md Ali M.A.; Syahirul Amin Megat Ali M.; Megat Tajuddin M.Z.; Younis M.A.A.
Published: (2022) -
An Improved Pheromone-Based Kohonen Self-Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets
by: Ahmad A.; Yusof R.; Zulkifli N.S.A.; Ismail M.N.
Published: (2021) -
Comparisons of ADABOOST, KNN, SVM and logistic regression in classification of imbalanced dataset
by: Rahman H.A.A.; Wah Y.B.; He H.; Bulgiba A.
Published: (2015)