Hate speech detection in Vietnamese on social network sites
This research recommend two types of model: SVM, and XGBoost. The results show that accuracy score of XGBoost is better than SVM (93.72% and 91.37% respectively). Therefore, this research recommend XGBoost is better model.
Saved in:
主要作者: | Le, Ngoc Nhung |
---|---|
其他作者: | Tran, Thi Oanh |
格式: | Final Year Project |
語言: | English |
出版: |
H. : ĐHQGHN
2020
|
主題: | |
在線閱讀: | http://repository.vnu.edu.vn/handle/VNU_123/97898 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
機構: | Vietnam National University, Hanoi |
語言: | English |
相似書籍
-
Determining Linguistic Features of Hate Speech from 2016 Philippine Election-Related Tweets
由: Enriquez, Raphael Christen K., et al.
出版: (2023) -
Identifying hate speech trends and prevention in Indonesia: a cross-case comparison
由: Alexandra, Lina A., et al.
出版: (2024) -
On explaining multimodal hateful meme detection models
由: HEE, Ming Shan, et al.
出版: (2022) -
Disentangling hate in online memes
由: LEE, Ka Wei, Roy, et al.
出版: (2021) -
Regulating online hate speech: The Singapore experiment
由: CHEN, Siyuan
出版: (2023)