@InProceedings{deshmane-friedrichs:2017:SemEval,
  author    = {Deshmane, Amit Ajit  and  Friedrichs, Jasper},
  title     = {TSA-INF at SemEval-2017 Task 4: An Ensemble of Deep Learning Architectures Including Lexicon Features for Twitter Sentiment Analysis},
  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     = {802--806},
  abstract  = {This paper describes the submission of
	team TSA-INF to SemEval-2017 Task 4
	Subtask A. The submitted system is an
	ensemble of three varying deep learning
	architectures for sentiment analysis. The
	core of the architecture is a convolutional
	neural network that performs well on text
	classification as is. The second subsystem
	is a gated recurrent neural network implementation.
	Additionally, the third system
	integrates opinion lexicons directly into a
	convolution neural network architecture.
	The resulting ensemble of the three architectures
	achieved a top ten ranking with
	a macro-averaged recall of 64.3%. Additional
	results comparing variations of
	the submitted system are not conclusive
	enough to determine a best architecture,
	but serve as a benchmark for further implementations.},
  url       = {http://www.aclweb.org/anthology/S17-2135}
}