Clickbait Identification using Neural Networks

Understand

This paper presents the results of our participation in the Clickbait Detection Challenge 2017.

• The system relies on a fusion of neural networks, incorporating different types of available informations.
• It does not require any linguistic preprocessing, and hence generalizes more easily to new domains and languages.
• The final combined model achieves a mean squared error of 0.0428, an accuracy of 0.826, and a F1 score of 0.564.