Comparative Analysis of SVM, XGBoost and Neural Network on Hate Speech Classification
In social media, it is found that hate speech is conveyed in the form of text, images and videos, as a result it can provoke certain people to do things that are against the law and harm other person. Therefore, it is necessary to make early detection of hate speech by utilizing machine learning alg...
Saved in:
Main Author: | Suwarno Liang |
---|---|
Format: | article |
Language: | ID |
Published: |
Ikatan Ahli Indormatika Indonesia
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/5fcf6029a49c4f0e852b30fcba14cc8f |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Optimasi Parameter Support Vector Machine Berbasis Algoritma Firefly Pada Data Opini Film
by: Styawati, et al.
Published: (2021) -
Sentiment Analysis of Work from Home Activity using SVM with Randomized Search Optimization
by: Fatihah Rahmadayana, et al.
Published: (2021) -
The classification of EEG-based wink signals: A CWT-Transfer Learning pipeline
by: Jothi Letchumy Mahendra Kumar, et al.
Published: (2021) -
GENDER CLASSIFICATION ON SKELETAL REMAINS: EFFICIENCY OF METAHEURISTIC ALGORITHM METHOD AND OPTIMIZED BACK PROPAGATION NEURAL NETWORK
by: Nurul Liyana Hairuddin, et al.
Published: (2020) -
Emotion Classification in Spanish: Exploring the Hard Classes
by: Aiala Rosá, et al.
Published: (2021)