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
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.- Anthology ID:
- S17-2100
- Volume:
- Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver, Canada
- Editors:
- Steven Bethard, Marine Carpuat, Marianna Apidianaki, Saif M. Mohammad, Daniel Cer, David Jurgens
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 611–615
- Language:
- URL:
- https://aclanthology.org/S17-2100
- DOI:
- 10.18653/v1/S17-2100
- Cite (ACL):
- Edilson Anselmo Corrêa Júnior, Vanessa Queiroz Marinho, and Leandro Borges dos Santos. 2017. NILC-USP at SemEval-2017 Task 4: A Multi-view Ensemble for Twitter Sentiment Analysis. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 611–615, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- NILC-USP at SemEval-2017 Task 4: A Multi-view Ensemble for Twitter Sentiment Analysis (Corrêa Júnior et al., SemEval 2017)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/S17-2100.pdf
- Code
- edilsonacjr/semeval2017