Detecting Spam Reviews on Vietnamese E-Commerce Websites

被引：0
|
作者：
Co Van Dinh [1 ,2 ]
Luu, Son T. [1 ,2 ]
Anh Gia-Tuan Nguyen [1 ,2 ]
机构：
[1] Univ Informat Technol, Ho Chi Minh City, Vietnam
[2] Vietnam Natl Univ, Ho Chi Minh City, Vietnam
来源：
INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2022, PT I | 2022年 / 13757卷
关键词：
Spam reviews; Text classification; Deep neural models; Transformer models; Dataset; Annotation guidelines; AGREEMENT;
D O I：
10.1007/978-3-031-21743-2_48
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The reviews of customers play an essential role in online shopping. People often refer to reviews or comments of previous customers to decide whether to buy a new product. Catching up with this behavior, some people create untruths and illegitimate reviews to hoax customers about the fake quality of products. These are called spam reviews, confusing consumers on online shopping platforms and negatively affecting online shopping behaviors. We propose the dataset called ViSpamReviews, which has a strict annotation procedure for detecting spam reviews on e-commerce platforms. Our dataset consists of two tasks: the binary classification task for detecting whether a review is spam or not and the multi-class classification task for identifying the type of spam. The PhoBERT obtained the highest results on both tasks, 86.89%, and 72.17%, respectively, by macro average F1 score.
引用
收藏
页码：595 / 607
页数：13
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