NILC-USP at SemEval-2017 Task 4: A Multi-view Ensemble for Twitter Sentiment Analysis
Edilson Anselmo Corrêa Júnior, Vanessa Queiroz Marinho, Leandro Borges dos Santos · 2017
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.