Steve Martin at SemEval-2019 Task 4: Ensemble Learning Model for Detecting Hyperpartisan News
Youngjun Joo, Inchon Hwang · 2019
This paper describes our submission to task 4 in SemEval 2019, i.e., hyperpartisan news detection.Our model aims at detecting hyperpartisan news by incorporating the stylebased features and the content-based features.We extract a broad number of feature sets and use as our learning algorithms the GBDT and the n-gram CNN model.Finally, we apply the weighted average for effective learning between the two models.Our model achieves an accuracy of 0.745 on the test set in subtask A.