The Sally Smedley Hyperpartisan News Detector at SemEval-2019 Task 4
Kazuaki Hanawa, Shota Sasaki, Hiroki Ouchi, Jun Suzuki, Kentaro Inui · 2019
This paper describes our system submitted to the formal run of SemEval-2019 Task 4: Hyperpartisan news detection.Our system is based on a linear classifier using several features, i.e., 1) embedding features based on the pre-trained BERT embeddings, 2) article length features, and 3) embedding features of informative phrases extracted from the by-publisher dataset.Our system achieved 80.9% accuracy on the test set for the formal run and got the 3rd place out of 42 teams.