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

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2019

Autores

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

Ata de Conferência Internacional

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

Páginas: 999-1003

Indexação

Crossref

Classificação Científica

CORDIS: Humanidades

Outras Informações

ID Authenticus: 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%.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 5