NLP@UIT at SemEval-2019 Task 4: The Paparazzo Hyperpartisan News Detector
Duc-Vu Nguyen, Thin Van Dang, Ngan Luu-Thuy Nguyen · 2019
This paper describes the system of NLP@UIT that participated in Task 4 of SemEval-2019.We developed a system that predicts whether an English news article follows a hyperpartisan argumentation.Paparazzo is the name of our system and is also the code name of our team in Task 4 of SemEval-2019.The Paparazzo system, in which we use tri-grams of words and hepta-grams of characters, officially ranks thirteen with an accuracy of 0.747.Another system of ours, which utilizes trigrams of words, tri-grams of characters, trigrams of part-of-speech, syntactic dependency sub-trees, and named-entity recognition tags, achieved an accuracy of 0.787 and is proposed after the deadline of Task 4.