@InProceedings{laskari-sanampudi:2017:SemEval,
  author    = {Laskari, Naveen Kumar  and  Sanampudi, Suresh Kumar},
  title     = {TWINA at SemEval-2017 Task 4: Twitter Sentiment Analysis with Ensemble Gradient Boost Tree Classifier},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {659--663},
  abstract  = {This paper describes the TWINA system, with which we participated in
	SemEval-2017 Task 4B (Topic Based Message Polarity Classification -- Two point
	scale) and 4D (two-point scale Tweet quantification). We implemented ensemble
	based Gradient Boost Trees classification method for both the tasks. Our system
	could perform well for the task 4D and ranked 13th among 15 teams, for the task
	4B our model ranked 23rd position.},
  url       = {http://www.aclweb.org/anthology/S17-2109}
}