UBC-NLP at SemEval-2019 task 4: Hyperpartisan news detection with attention-based Bi-LSTMs

Abstract

We present our deep learning models submitted to the SemEval-2019 Task 4 competition focused at Hyperpartisan News Detection. We acquire best results with a Bi-LSTM network equipped with a self-attention mechanism. Among 33 participating teams, our submitted system ranks top 7 (65.3% accuracy) on the labels-by-publisher sub-task and top 24 out of 44 teams (68.3% accuracy) on the labels-by-article sub-task (65.3% accuracy). We also report a model that scores higher than the 8th ranking system (78.5% accuracy) on the labels-by-article sub-task.