GANs for Semi-Supervised Opinion Spam Detection

@article{Stanton2019GANsFS,
  title={GANs for Semi-Supervised Opinion Spam Detection},
  author={Gray Stanton and Athirai Aravazhi Irissappane},
  journal={ArXiv},
  year={2019},
  volume={abs/1903.08289}
}
Online reviews have become a vital source of information in purchasing a service (product). Opinion spammers manipulate reviews, affecting the overall perception of the service. A key challenge in detecting opinion spam is obtaining ground truth. Though there exists a large set of reviews, only a few of them have been labeled spam or non-spam. We propose spamGAN, a generative adversarial network which relies on limited labeled data as well as unlabeled data for opinion spam detection. spamGAN… Expand
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