@InProceedings{sengupta-pedersen:2019:S19-2,
  author    = {Sengupta, Saptarshi  and  Pedersen, Ted},
  title     = {Duluth at SemEval-2019 Task 4: The Pioquinto Manterola Hyperpartisan News Detector},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {949--953},
  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.},
  url       = {http://www.aclweb.org/anthology/S19-2162}
}