A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is
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