@InProceedings{muller-EtAl:2017:SemEval,
  author    = {M\"{u}ller, Simon  and  Huonder, Tobias  and  Deriu, Jan  and  Cieliebak, Mark},
  title     = {TopicThunder at SemEval-2017 Task 4: Sentiment Classification Using a Convolutional Neural Network with Distant Supervision},
  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     = {766--770},
  abstract  = {In this paper, we propose a classifier for
	predicting topic-specific sentiments of English
	Twitter messages. Our method is
	based on a 2-layer CNN.With a distant supervised
	phase we leverage a large amount
	of weakly-labelled training data. Our system
	was evaluated on the data provided
	by the SemEval-2017 competition in the
	Topic-Based Message Polarity Classification
	subtask, where it ranked 4th place.},
  url       = {http://www.aclweb.org/anthology/S17-2129}
}