Team Fernando-Pessa at SemEval-2019 Task 4: Back to Basics in Hyperpartisan News Detection
André Ferreira Cruz, Gil Rocha, Rui Sousa‐Silva, Henrique Lopes Cardoso · 2019
This paper describes our submission 1 to the SemEval 2019 Hyperpartisan News Detection task.Our system aims for a linguistics-based document classification from a minimal set of interpretable features, while maintaining good performance.To this goal, we follow a feature-based approach and perform several experiments with different machine learning classifiers.On the main task, our model achieved an accuracy of 71.7%, which was improved after the task's end to 72.9%.We also participate in the meta-learning sub-task, for classifying documents with the binary classifications of all submitted systems as input, achieving an accuracy of 89.9%.