Publikation

Clickbait Identification using Neural Networks

Philippe Thomas

Clickbait Challenge 2017 2017.

Abstrakt

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 F1score of 0.564. According to the official evaluation metric the system ranked 6th of the 13 participating teams.

Projekte

Weitere Links

1710.08721.pdf (pdf, 145 KB)

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence