@InProceedings{correajunior-marinho-dossantos:2017:SemEval,
  author    = {Corr\^{e}a J\'{u}nior, Edilson Anselmo  and  Marinho, Vanessa Queiroz  and  dos Santos, Leandro Borges},
  title     = {NILC-USP at SemEval-2017 Task 4: A Multi-view Ensemble for Twitter Sentiment Analysis},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {611--615},
  abstract  = {This paper describes our multi-view ensemble approach to SemEval-2017 Task 4 on
	Sentiment Analysis in Twitter, specifically, the Message Polarity
	Classification subtask for English (subtask A). Our system is a voting
	ensemble, where each base classifier is trained in a different feature space.
	The first space is a bag-of-words model and has a Linear SVM as base
	classifier. The second and third spaces are two different strategies of
	combining word embeddings to represent sentences and use a Linear SVM and a
	Logistic Regressor as base classifiers. The proposed system was ranked 18th out
	of 38 systems considering F1 score and 20th considering recall.},
  url       = {http://www.aclweb.org/anthology/S17-2100}
}