Detecting Spam Reviews on Vietnamese E-commerce Websites

Co Van Dinh, Son T. Luu, Anh Gia-Tuan Nguyen
7/27/2022
cs.CLcs.AI

No official code found. Best implementation: sonlam1102/vispamdetection (17 stars, last commit 2026-01-28).

Abstract

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.

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Code Implementations(1)

sonlam1102/vispamdetectionCommunity100%

Spam Reviews Detection on Vietnamese E-commerce website

173Jupyter NotebookJul 27, 20228 months ago

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Cite this paper

@article{dinh2022detecting,
  title  = {Detecting Spam Reviews on Vietnamese E-commerce Websites},
  author = {Co Van Dinh and Son T. Luu and Anh Gia-Tuan Nguyen},
  year   = {2022},
  eprint = {2207.14636},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2207.14636v2}
}

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