Abstract
This paper describes the Pioquinto Manterola Hyperpartisan News Detector, which participated in SemEval-2019 Task 4. Hyperpartisan news is highly polarized and takes a very biased or one-sided view of a particular story. We developed two variants of our system, the more successful was a Logistic Regression classifier based on unigram features. This was our official entry in the task, and it placed 23rd of 42 participating teams. Our second variant was a Convolutional Neural Network that did not perform as well.
| Original language | English (US) |
|---|---|
| Title of host publication | NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 949-953 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781950737062 |
| State | Published - 2019 |
| Event | 13th International Workshop on Semantic Evaluation, SemEval 2019, co-located with the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019 - Minneapolis, United States Duration: Jun 6 2019 → Jun 7 2019 |
Publication series
| Name | NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop |
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Conference
| Conference | 13th International Workshop on Semantic Evaluation, SemEval 2019, co-located with the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019 |
|---|---|
| Country/Territory | United States |
| City | Minneapolis |
| Period | 6/6/19 → 6/7/19 |
Bibliographical note
Publisher Copyright:© 2019 Association for Computational Linguistics