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I2RNTU at SemEval-2016 Task 4: Classifier Fusion for Polarity Classification in Twitter

Zhengchen Zhang, Chen Zhang, wu fuxiang, Dongyan Huang, Weisi Lin, Minghui Dong
2016 Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)  

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https://web.archive.org/web/20190223063550/http://www.aclweb.org:80/anthology/S16-1008

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The fusion system achieved 59.63% accuracy on the 2016 test set of SemEval2016 Task 4, Subtask A.  ...  In this work, we apply classifier fusion to tweet polarity identification problem. The task is to predict whether the emotion hidden in a tweet is positive, neutral, or negative.  ...  Introduction The I2RNTU system works on the Subtask A: Message Polarity Classification in Twitter of SemEval-2016 Task 4: the Sentiment Analysis in Twitter (Nakov et al., 2016) .  ... 
doi:10.18653/v1/s16-1008 dblp:conf/semeval/ZhangZWHLD16 fatcat:yofo7i3h5ncj3gqn533iefqnfy
Citation

Zhengchen Zhang, Chen Zhang, wu fuxiang, Dongyan Huang, Weisi Lin, Minghui Dong. "I2RNTU at SemEval-2016 Task 4: Classifier Fusion for Polarity Classification in Twitter." Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016) (2016) 71-78