The Good, the Bad and the Bait: Detecting and Characterizing Clickbait on YouTube

@article{Zannettou2018TheGT,
  title={The Good, the Bad and the Bait: Detecting and Characterizing Clickbait on YouTube},
  author={Savvas Zannettou and Sotirios P. Chatzis and Kostantinos Papadamou and Michael Sirivianos},
  journal={2018 IEEE Security and Privacy Workshops (SPW)},
  year={2018},
  pages={63-69}
}
The use of deceptive techniques in user-generated video portals is ubiquitous. Unscrupulous uploaders deliberately mislabel video descriptors aiming at increasing their views and subsequently their ad revenue. This problem, usually referred to as "clickbait," may severely undermine user experience. In this work, we study the clickbait problem on YouTube by collecting metadata for 206k videos. To address it, we devise a deep learning model based on variational autoencoders that supports the… Expand
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