Team Fernando-Pessa at SemEval-2019 Task 4: Back to Basics in Hyperpartisan News Detection

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

André Cruz (Author) FEUP; Gil Rocha (Author) FEUP; Rui Sousa Silva (Author) FLUP; Henrique Lopes Cardoso (Author) FEUP

Conference proceedings International

Title: Proceedings of the 13th International Workshop on Semantic Evaluation

Pages: 999-1003

Indexing

Crossref

Scientific classification

CORDIS: Humanities

Other information

Authenticus ID: P-00W-RHX

DOI: 10.18653/v1/s19-2173

Abstract (EN): This paper describes our submission1 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%.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 5