Machine Learning Based Detection of Clickbait Posts in Social Media

@article{Cao2017MachineLB,
  title={Machine Learning Based Detection of Clickbait Posts in Social Media},
  author={Xinyue Cao and Thai Le and Jason Zhang},
  journal={CoRR},
  year={2017},
  volume={abs/1710.01977}
}
Clickbait (headlines) make use of misleading titles that hide critical information from or exaggerate the content on the landing target pages to entice clicks. As clickbaits often use eye-catching wording to attract viewers, target contents are often of low quality. Clickbaits are especially widespread on social media such as Twitter, adversely impacting user experience by causing immense dissatisfaction. Hence, it has become increasingly important to put forward a widely applicable approach to… CONTINUE READING
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The Clickbait Challenge 2017: Towards a Regression Model for Clickbait Strength

M. Potthast, T. Gollub, M. Hagen, B. Stein
In Proceddings of the Clickbait Chhallenge, • 2017

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