SUPPORT VECTOR MACHINE IMPLEMENTATION FOR RACIAL CYBERBULLYING SENTIMENT ANALYSIS IN YOUTUBE COMMENTS
This study focuses on developing a model for detecting and classifying cyberbullying, particularly related to hate speech based on ethnicity, religion, race, and intergroup relations, using Support Vector Machine (SVM) and TF-IDF weighting. Data was collected from YouTube comments and categorized...
Saved in:
Main Author: | Made Alit Adinugraha, Dewa |
---|---|
Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/86873 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Similar Items
-
Transductive support vector machines for cross-lingual sentiment classification.
by: Nguyen, Thi Thuy Linh
Published: (2017) -
Sentiment classification with support vector machines and multiple kernel functions
by: Tanasanee Phienthrakul, et al.
Published: (2018) -
ANALYSIS OF THE EFFECT OT TWITTER SENTIMENT ON BITCOIN PRICES USING THE SUPPORT VECTOR MACHINE AND MAXIMUM ENTROPY METHODS
by: Isyafira, Dyah -
IMPLEMENTATION OF TOPOLOGICAL DATA ANALYSIS AND SUPPORT VECTOR MACHINE FOR MNIST DATASET CLASSIFICATION
by: Nilam Sari, Nur -
IMPLEMENTATION OF MACHINE LEARNING SUPPORT VECTOR MACHINE ALGORITHM IN FRAUD DETECTION SYSTEM
by: Muhammad Ghifary K, Abidzar