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NILC-USP at SemEval-2017 Task 4: A Multi-view Ensemble for Twitter Sentiment Analysis

Abstract · Apr 7, 2017 15:27 ·

tweets base linear svm logistic classifiers section spaces considering cs-cl cs-lg

Arxiv Abstract

  • Edilson A. Corrêa Jr.
  • Vanessa Queiroz Marinho
  • Leandro Borges dos Santos

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.

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