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PUT at SemEval-2016 Task 4: The ABC of Twitter Sentiment Analysis
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)
This paper describes a classification system that participated in SemEval-2016 Task 4: Sentiment Analysis in Twitter. The proposed approach competed in subtasks A, B, and C, which involved tweet polarity classification, tweet classification according to a two-point scale, and tweet classification according to a five-point scale. Our system is based on an ensemble consisting of Random Forests, SVMs, and Gradient Boosting Trees, and involves the use of a wide range of features including: ngrams,doi:10.18653/v1/s16-1018 dblp:conf/semeval/LangoBS16 fatcat:eodrzamxabdppcavkn4ivwhicq