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    <abstract>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.</abstract>
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%0 Conference Proceedings
%T NLP@UIT at SemEval-2019 Task 4: The Paparazzo Hyperpartisan News Detector
%A Nguyen, Duc-Vu
%A Dang, Thin
%A Nguyen, Ngan
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F nguyen-etal-2019-nlp
%X 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.
%R 10.18653/v1/S19-2167
%U https://aclanthology.org/S19-2167
%U https://doi.org/10.18653/v1/S19-2167
%P 971-975

Markdown (Informal)

[NLP@UIT at SemEval-2019 Task 4: The Paparazzo Hyperpartisan News Detector](https://aclanthology.org/S19-2167) (Nguyen et al., SemEval 2019)

• NLP@UIT at SemEval-2019 Task 4: The Paparazzo Hyperpartisan News Detector (Nguyen et al., SemEval 2019)

ACL

• Duc-Vu Nguyen, Thin Dang, and Ngan Nguyen. 2019. NLP@UIT at SemEval-2019 Task 4: The Paparazzo Hyperpartisan News Detector. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 971–975, Minneapolis, Minnesota, USA. Association for Computational Linguistics.